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Systematic and timely documentation of triggered (i.e. event) landslides is fundamental to build extensive datasets worldwide that may help define and/or validate trends in response to climate change. More in general, preparation of landslide inventories is a crucial activity since it provides the basic data for any subsequent analysis. In this work we present an event landslide inventory map (E-LIM) that was prepared through a systematic reconnaissance field survey in about 1 month after an extreme rainfall event hit an area of about 5000 km2 in the Marche-Umbria regions (central Italy). The inventory reports evidence of 1687 triggered landslides in an area of ~550 km2. All slope failures were classified according to type of movement and involved material, and documented with field pictures, wherever possible. The database of the inventory described in this paper as well as the collection of selected field pictures associated with each feature is publicly available at figshare. [ABSTRACT FROM AUTHOR]

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Heavy rainfall and precipitation play a massive role in shaping the socio-agricultural landscape of a country. Being one of the key indicators of climate change, natural disasters, and of the general topology of a region, rainfall prediction is a gift of estimation that can be used for multiple beneficial causes. Machine learning has an impressive repertoire in aiding prediction and estimation of rainfall. This paper aims to find the effect of ensemble learning, a subset of machine learning, on a rainfall prediction dataset, to increase the predictability of the models used. The classification models used in this paper were tested once individually, and then with applied ensemble techniques like bagging and boosting, on a rainfall dataset based in Australia. The objective of this paper is to demonstrate a reduction in bias and variance via ensemble learning techniques while also analyzing the increase or decrease in the aforementioned metrics. The study shows an overall reduction in bias by an average of 6% using boosting, and an average reduction in variance by 13.6%. Model performance was observed to become more generalized by lowering the false negative rate by an average of more than 20%. The techniques explored in this paper can be further utilized to improve model performance even further via hyper-parameter tuning. [ABSTRACT FROM AUTHOR]

It is often hypothesized that adaptive capacity leads to increased yield. However, the veracity of this assumption in quantitative terms has largely remained understudied by researchers. Also, adaptation depends on the vulnerability of the agricultural sector, climate risks, biocapacity of the area, readiness and adaptive capacities of stakeholders. Adaptation can only take place if stakeholders are ready to respond and resources are also available. To understand these relationships, the paper examined the impacts of climate change, food vulnerability, adaptive capacity, biocapacity and readiness on yields of major cereal crops in thirty-five African countries. We used the panel autoregressive distributive lag model to analyse publicly available panel data obtained from FAOSTAT, Global Foot Print Network, and Notre Dame Adaptation Index databases, and World Bank Group Climate Change Knowledge Portal. The results show that biocapacity, adaptive capacity, food sector vulnerability, and temperature decreased rice yield in the long. Biocapacity increased maize and sorghum yields, while adaptive capacity decreased their yields in the long run. Food sector vulnerability and temperature decreased maize yield in the long run, while temperature increased sorghum yield in the long run. The results suggest that improvement in adaptive capacity is an important policy tool to increase the yield of some cereal crops. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper analyzed the spatial-temporal variability of rainfall and detection of potential trend change point over Kosi River basin, Kumaon Lesser Himalaya, India, using long-term gridded data and historical metrological records in hilly river basin of Uttarakhand. The Mann-Kendall (MK) test was used to determine the spatio-temporal trend using IMD (0.25° × 0.25°) gridded rainfall data during 1901–2015. The Theil-Sen slope was used to determine the magnitude of change in rainfall during the study period. Additionally, the sequential Mann-Kendal (SQ-MK) test and Pettitt's test has been used to find the abrupt change point in historical time series (1980–2019). Results of the study show that northeastern and southwestern parts of the Kosi River basin exhibit a statistically significant decreasing trend in both June and July months at 5% significance level. Northeastern and southwestern parts of the basin exhibit a statistically significant decreasing trend for monthly and annual rainfall. The range of Sen's slope values varies from −0.6 to −6.6 mm/year. Based on the analysis of SQ-MK and Pettitt's test, the change points for Almora, Mukteshwar, and Hawalbagh were 1991, 2004, and 1998 respectively. Therefore, this paper attempts to provide actionable knowledge for irrigation water planning, water management, and soil and water conservation for Uttarakhand. [ABSTRACT FROM AUTHOR]

The latest report by the Intergovernmental Panel on Climate Change (IPCC) warns of an increase in heavy rainfall events due to global warming and climate change, which can result in significant economic costs for insurance companies and businesses. To address this challenge, insurance companies are focusing on developing new risk management strategies and offering new products such as flood insurance. However, the article argues that effective and feasible coordination shortens recovery time and can therefore drastically reduce the financial costs of a crisis—that is, the insurance costs. The paper analyses the deficit in crisis management during heavy rain events in Germany, based on the 2021 Ahr valley flood. The analysis is conducted based on document analysis and interviews and focuses on three areas of deficit: coordination between crisis staffs and (1) civil society, (2) emergency responders, and (3) political leaders. The paper highlights the importance of coordination during a crisis, which can help to address the crisis more efficiently and effectively, minimise damage and get communities back on their feet faster. The paper recommends policy changes to improve interface management and disaster management coordination. [ABSTRACT FROM AUTHOR]

Quantifying the extent of change in climatic and hydrological variables in the past and the future is essential for climate change-resilient development, especially in the climate change sensitive region of Nepal. This paper analyzed future climatic trends and extremes, historical hydrological extremes and their linkage with historical precipitation extremes, and discussed the impacts of climate change on various sectors in the less-studied Small and Medium-sized Eastern River Basins (SMERB) of Nepal. Applying an ensemble of five Coupled Model Intercomparison Project phase 6 (CMIP6) global climate models (GCMs), we evaluated 10 precipitation and 13 temperature extreme indices using Climpact2 for the historical (1979–2020), near-future (2021–2045), mid-future (2046–2070) and far-future (2071–2100) under two Shared Socioeconomic Pathway (SSP), SSP245 and SSP585. Hydrological extreme indices were assessed using Indicators of Hydrologic Alteration tool. Projected climate revealed significant increase (9–73%) in annual and seasonal rainfall except winter; frequent intense rainfall extremes but prolonged dry spells; significant increasing minimum and maximum temperature trends (0.4–5 °C); rise in extreme heat events; increasing minimum and maximum discharge extreme trends in most hydrological stations; as well as strong association between maximum 1 day precipitation (Rx1day) and 1 day max flow for all stations. Growing dry periods but intense rainfall in few wet days, coupled with warming pattern all-over SMERB with frequent extreme events indicate high risk for future climate-related disasters. The harsher climate will potentially have damaging implications, especially in climate-induced disasters, food security, and water and sanitation infrastructure. [ABSTRACT FROM AUTHOR]

This paper explores the operationalization of climate-related indicators in violent conflict research. The climate-conflict narrative gained traction in recent decades and climate change is often referred to as a 'threat multiplier' by both policy makers and scholars. Yet, the relationships between climate-related phenomena and violent conflict are complex and context-specific. However, limited attention has been given to the climatic indicators applied in climate-conflict research. This paper addresses that gap by analyzing 32 studies published from 2004 to 2020 on the operationalization of climatic indicators and their relationship with violent conflict. It first categorizes climate indicators operationalization into five clusters: natural disasters, basic climate variability, advanced climate variability, freshwater availability, and the ENSO. The study evaluates the climate indicators for each cluster and shows that at an aggregate level these clusters examine 68 different climate representations. When paired with their respective conflict types, it finds a total of 113 climate-conflict combinations. Most operationalizations represent various forms of climate-related phenomena and variability rather than climate change. Some indicators are advancements over time, for example moving from changes in average rainfall to standardized precipitation indices. However, other indicators refer to various natural processes, making it challenging to determine whether climatic variability impacts conflict. The paper then demonstrates a discrepancy between the pathways through which climate may affect violent conflict and the representation of these pathways in the selected climate indicators. It discusses how the selection and operationalization of climate indicators requires careful consideration, and the phenomena researched should be well-specified in research findings. [ABSTRACT FROM AUTHOR]

Understanding the future patterns of precipitation behaviour in unique geographical areas, largely determined by their orography and local scale, can help lay the foundations for a new precipitation model for the design of the city's main urban drainage infrastructures (intensity-duration-frequency curves, mathematical functions that relate precipitation intensity to duration and frequency of occurrence, hereafter IDF, for the short-, medium- and long-term future). This will definitely contribute to the improvement of the city's resilience to the effects of climate change. In this paper, the projections of a subset of climate change models from both the sixth phase of the Coupled Model Intercomparison Project (CMIP6; with a total of 5 simulations) and Euro-CORDEX (for a set of 51 simulations) have been adjusted to the municipality of Alicante (in the southeast of Spain), using the Climadjust tool (climadjust.com). These projections contain different climatic variables. The rainfall variable has been used to derive a new framework of boundary conditions to help design more resilient infrastructure for torrential rainfall events and urban flooding. The projections corresponding to three climate change scenarios (CMIP6: SSP1-2.6, SSP2-4.5, SSP5-8.5; and Euro-CORDEX: RCP2.6, RCP4.5, RCP8.5) are considered with daily resolution and, by applying statistical techniques of temporal disaggregation (by means of a cascade model), hourly (and sub-hourly, reaching 30-min resolution) disaggregation. The results at hourly and 30-min resolutions are used to construct IDF curves of future climate, grouped into short-term (years 2015 to 2040), medium-term (years 2041 to 2070) and long-term (years 2071 to 2100) sub-scenarios. The selected future climate IDFs for an adverse climate change scenario (SSP2-4.5 and SSP5-8.5) show increases in rainfall intensities, higher the shorter the rainfall duration, for return periods greater than or equal to 25 years, whereas for return periods under 25 years the current IDFs can be representative of future scenarios. Current calculations and future projection of the torrentiality index for severe climate change scenarios, as well as the climate change factors, show an increase in the frequency and magnitude of the heaviest rainfall. This fact corroborates the hypotheses of greater general torrentiality in future rainfall in this specific area of the Spanish Mediterranean coast. [ABSTRACT FROM AUTHOR]

Climate change has appeared as a major issue in recent years, and its impacts are seen multi-dimensionally. The local people are the key eyewitnesses of climate change, although the discourse is disciplinary, geographic, and gender biased. In this context, this paper documents the perceptions and narratives of the Tamang, an Indigenous people, who live on the outskirts of the Kathmandu Valley. This is an ethnographic study and applied quantitative and qualitative data. The data of the study were gathered using triangulation methods, i.e., household questionnaire survey (HQS), key informant interview (KII), and focus group discussion (FGD). A total of 94 HQS, nine KII, and three FGD were carried out in 2018 in three sample sites in the outskirts of the valley. The station-based observed climatic data from 1969 to 2022 were collected from the Department of Hydrology and Meteorology. The observed data shows increasing annual rainfall and temperature in Kathmandu; however, the rate of temperature increase is much larger. Seasonal precipitation shows decreasing rainfall in post-monsoon, which enhances the winter drought. The Tamang are the key eyewitness of the changes in climate and this knowledge is inbuilt with their memories which are closely bound to the place. Hence, the life history of elderly people can be an appropriate way of understanding the micro-climatic changes in the local context, which largely failed or ignored to document in scientific or macro-level assessments. [ABSTRACT FROM AUTHOR]

In the paper, the frequency and spatial distribution of atmospheric and hydrological droughts over the territory of Belarus in 1945–2020 is assessed. Aridity is evaluated using the standardized precipitation and streamflow indices (SPI and SSFI). Trends in monthly total precipitation are determined, the features of the streamflow formation during the open-channel period are revealed. The frequency of anticyclones that determines hydrometeorological conditions on the territory of Belarus is calculated. The statistically significant increase in the number of the days with anticyclonic weather over the country during the warm season is found. The increasing frequency of dry conditions in summer months against the background of a rise in the precipitation intensity is highlighted. A simultaneous increase in the frequency of very-low-flow periods on rivers and an increase in the height of warm rainfall floods in some river basins are revealed. [ABSTRACT FROM AUTHOR]

Rural populations are particularly exposed to increasing weather variability, notably through agriculture. In this paper, we exploit longitudinal data for Turkish provinces from 2008 to 2018 together with precipitation records over more than 30 years to quantify how variability in a standardized precipitation index (SPI) affects out-migration as an adaptation mechanism. Doing so, we document the role of three potential causal channels: per capita income, agricultural output, and local conflicts. Our results show that negative SPI shocks (droughts) are associated with higher out-migration in rural provinces. A mediated-moderator approach further suggests that changes in per capita income account for more than one quarter of the direct effect of droughts on out-migration, whereas agricultural output is only relevant for provinces in the upper quartile of crop production. Finally, we find evidence that local conflict fatalities increase with drought and trigger out-migration, although this channel is distinct from the direct effect of SPI shocks on out-migration. [ABSTRACT FROM AUTHOR]

The paper presents potential impacts of climate change on rainwater tanks outcomes such as water savings, reliability and water savings efficiency under two projected climate change scenarios; RCP4.5 and RCP8.5 utilising a case study using rainfall data from four stations within the city of Brisbane, Australia. Historical rainfall data were collected from the Australian Bureau of Meteorology website for the selected stations. Projected daily rainfall data were collected from Australian government data portal for the same stations within Brisbane. Using an earlier developed daily water balance model, eTank potential annual water savings were calculated for several weather and climate change scenarios with varied roof areas and rainwater demandValues of 'Seasonality Index (SI)', a commonly used factor representing rainfall variability within a year, were explored to validate earlier developed relationships between SI and water savings efficiency through rainwater tanks. It is found that in most cases water savings in future periods are expected to decrease and such decrease is not necessarily attributed to the expected decrease in rainfall amounts in future, rather also affected by future reductions in rainwater tank reliability. Linear relationships between potential future water savings and reliabilities for all the stations are found. Relationship between SI and water savings efficiency was established, and it is found that the relationship slightly varies with an earlier developed relationship using historical data. Compared to earlier established relationship, for lower SI values water savings efficiency is expected to become better, while for higher SI values the water savings efficiency is expected to become worse. Also, an increase of roof area from 100 m2 to 200 m2 will cause an average increase of water savings efficiency by 25% and an increase of rainwater usage from 200 L/day to 300 L/day will cause an average increase of water savings efficiency by 20%. [ABSTRACT FROM AUTHOR]

The rainfall over the Indian region, governed majorly by the monsoonal flow, is a point of research in the perspective of climate change. In this paper, we compute the change points in the rainfall series at every grid of the India Meteorological Department (IMD) daily gridded rainfall data for a period of 120 years (1901 to 2020). The map shows clearly demarcated regions indicating different zones, where the rainfall statistics have altered at different periods. It is observed that in a major part of central India, the shift in rainfall intensity is mainly associated with the time frame 1955–1965; in the Indo-Gangetic plain, the changes are found to be more recent (1990), while the latest changes (post 2000) are observed particularly for North Eastern region and some parts along the East Indian coast. The changeover years are significant at a 95% confidence level for most part of the Indian landmass. The causes may be surmised due to moisture transport from the Arabian Sea (Central India), the presence of aerosol (Gangetic Plain), and the possible revival of monsoon due to land–ocean gradient (Eastern coast and North East India). This is the first-ever study which provides a comprehensive daily rainfall change point map over India using 120 years of gridded station data. [ABSTRACT FROM AUTHOR]

The low-lying Vietnamese Mekong Delta (VMD) is a key agricultural production landscape increasingly threatened by anthropogenic stresses and climate change. Among the different threats, droughts caused by extreme events, climate change and upstream developments, affect the delta the most. This paper explores the relationship between the intensity, duration, and frequency of meteorological droughts and hydrological droughts using a range of indices. We used monthly rainfall and stream flow data for the period 1992–2021 to calculate the Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI), and the streamflow drought Index (SDI) for different time intervals. We found no observed time lag, and a strong correlation coefficient between upstream hydrological and downstream meteorological drought events assessed over long-term scales (i.e., 12-months). This is true for all downstream sites, except Ben Tre City. Hydrological drought events onset lagged 5–6-, 6-, and 3–4-month behind meteorological droughts at mid- and shorter assessment time scales (9-, 6-, 3-month). The average correlation coefficients between hydrological indices and meteorological indices at 9–3-month time scales ranged from moderate to weak. These findings shed light and advance the understanding of the progression of meteorological to hydrological droughts in the VMD. Our results aid the regional understanding of drought onset and the causative mechanisms at work, which is important for both medium- and long-term drought forecasting and adaptation planning. [ABSTRACT FROM AUTHOR]

The increasing frequency of extreme rainstorms due to climate changes calls for cost-effective methodologies to optimize drainage networks and flood risk mitigation practices. This paper presents an effective methodology that combines two well-known methods to optimize the drainage network design. The methodology uses the Harmony Search algorithm to identify the best solution for the drainage network and the simulations obtained through the Storm Water Management Model to verify the respect of the hydraulic constraints. The methodology is applied to the literature case study of Anytown, showing a significant reduction of 34.5% of the drainage network design cost compared with the common Rational Method. Moreover, the methodology is able to identify the optimum allocation and volumes of detention ponds for runoff control in case of variations in rainfall regime. The methodology allowed to prevent floods, by decreasing the channel filling degree. [ABSTRACT FROM AUTHOR]

Demographic outbursts and increased food demands invoke excessive use of pesticides in the agricultural field for increasing productivity which leads to the relentless decline of riverine health and its tributaries. These tributaries are connected to a plethora of point and non-point sources that transport pollutants including pesticides into the Ganga river's mainstream. Simultaneous climate change and lack of rainfall significantly increase pesticide concentration in the soil and water matrix of the river basin. This paper is intended to review the paradigm shift of pesticide pollution in the last few decades in the river Ganga and its tributaries. Along with this, a comprehensive review suggests the ecological risk assessment method which facilitates policy development, sustainable riverine ecosystem management, and decision-making. Before 2011, the total mixture of Hexachlorocyclohexane was found at 0.004–0.026 ng/mL in Hooghly, but now, the concentration has increased up to 0.465–4.132 ng/mL. Aftermath of critical review, we observed maximum residual commodities and pesticide contamination reported in Uttar Pradesh > West Bengal > Bihar > Uttara Khand possibly because of agricultural load, increasing settlement, and incompetency of sewage treatment plant in the reclamation of pesticide contamination. [ABSTRACT FROM AUTHOR]

Rainfall in the Moist Tropical Caribbean Region (MTCR) in Costa Rica occurs practically throughout the year, with the quarters June–August (JJA) and December–February (DJF) concentrating over 70% of annual rainfall. Contrarily, in March–April and September–October, it rains below 100 mm per month. This seasonal rainfall behavior makes the region ideal for producing bananas (Musa spp.) and pineapple (Ananas comosus) for export (10% and 8% of total exports in 2021, respectively). A national-scale study determined that agriculture in the MTCR is one of the most vulnerable sectors to climate changes. However, the climate in this region has been poorly studied so far. This research analyzed the spatial and temporal variability of annual, monthly, and seasonal (DJF, JJA, SO) rainfall in the MTCR and how they change in the study period based on quality-checked series of daily rainfall from 28 weather stations in two periods: 1985–2009 and 1997–2019. The results show that rainfall regimes in the region are variable in space and throughout the year, with peaks occurring close to the mountain range and minimum values close to the coast. Trends were statistically significant in the period 1985–2009 with a predominance of significant positive trends in DJF and significant negative trends in SO. No significant trends (positive or negative) were observed in the period 1997–2019. JJA rainfall has uneven regional distribution and presents a positive and significant trend in the mountain region. This paper contributes to filling the knowledge gap in rainfall seasonality, variability, and trends in a region where banana and pineapple commercial plantations are fundamental to the country's economy thus providing information to decision-making in the agri-food sector to reduce the negative impacts of changing rainfall regimes. [ABSTRACT FROM AUTHOR]

Climate change severely affects sub-Saharan African economies in several ways: increased temperatures, erratic rainfall variability patterns, and recurrent droughts and floods. Such adverse climate change effects may result in a greater incidence of crop pests, loss of soil moisture content, rapid soil nutrient depletion and substantial decreases in crop productivity and yields. These effects in combination with lack of access to improved, high-yielding crop varieties, limited agricultural extension services and poor access to irrigation infrastructure could further threaten access to food, limit export earnings and markedly lower net crop revenue. Several definitions, assessment approaches and methods for the concepts related to "vulnerability" and "adaptation" exist due to complex nature of climate impact and strategies used to deal with them. Based on the context of such studies, this paper reviews climate change risks, people's vulnerability to such risks as well as synthesize different approaches, methods and models used to assess vulnerability and adaptation in the area of agriculture in sub-Saharan Africa. As climate change effects are complex and site-specific, the understanding of several concepts, approaches and methods provides detailed information on farmers' vulnerability and adaptation process. Such information would be useful to inform adaptation interventions and agricultural policies that build farmers' resilience. [ABSTRACT FROM AUTHOR]

Under global warming and climate change (CC), the vulnerable piece of land is India's Eastern-Himalayan-Region (EHR), where millions' livelihood activities are at risk. Quantifying the degree of CC-induced vulnerability over the highly climate-sensitive mountain zone is challenging due to data inadequacy. This paper attempted to assess the CC perception of kiwifruit growers under EHR and the impact of CC on its cultivation. Perceived and scientific data were used for accurate decision-support information. The climatic variables of two locations were analyzed for trend using Mann–Kendall's test. Results suggested that the rainfall trend was found non-significant for both locations, but there was a negative trend during winter for Pasighat and during all seasons for Itanagar. Maximum temperature exhibited an increasing trend for annual, and minimum temperature showed an increasing trend across seasons for the Pasighat region. For the Itanagar region, the maximum temperature was found to have a significantly increasing trend in all seasons, while the minimum temperature showed an increasing trend during winter and annual seasons. Morning relative humidity showed an increasing trend for annual data for Pasighat, while annual evening relative humidity was significantly increased for Itanagar. The study shows that the indigenous farming communities were following shifting cultivation and diversifying their traditional agriculture to kiwifruit cultivation as an adaptation strategy. The community had a clear perception of CC trends and an inadequate perception of the impact on agriculture, therefore, engaging indigenous communities and other stakeholders to postulate a comprehensive adaptation and mitigation strategy for CC. [ABSTRACT FROM AUTHOR]

Agriculture is affected by climate change, such as extreme increases or decreases rainfall and temperature patterns. It is possible to research that effect by using trend analysis methodologies. This paper investigates trends of monthly total rainfall and mean temperature data of nine selected stations from agricultural regions of Turkey between 1969 and 2020. To the end, the classical Mann–Kendall, Innovative Trend Significance Test (ITST), and Innovative Polygon Trend Analysis (IPTA) with Star Graph methods providing the opportunity to examine seasonal behavior were used for trend analysis. The analysis reveals that about 96% of all monthly rainfall in the Mann-Kendall test has no trend. However, nearly all stations tend to decrease (increase) in November (September) in both innovative approaches. For temperature, it is seen that increasing trend or no trend dominated in general. There were increasing trends in the innovative approaches throughout the year except for April. Temperatures have increased significantly throughout the year in all regions over the last decades. With the help of IPTA, it was also concluded that the seasonal internal variability of rainfall over the entire time and in the last 30 years is quite complex and persists in all agricultural regions. The results show that irregular changes in rainfall and rising temperatures in all stations negatively affected crop yield and/or required more irrigation. In addition, according to the results obtained by comparing trend methods, innovative approaches are very insistent on determining of trend and provide additional information through a visual review of trend behaviors. [ABSTRACT FROM AUTHOR]

Climate change may cause adverse impact on agricultural production that could jeopardize food availability and security. In this paper, we investigate how changes in mean values and variability of weather variables may affect rice yield using panel data for 30 districts of Tamil Nadu State from 1971 to 2018. We estimate a fixed-effects regression model with panel-corrected standard errors. Results show that rainfall and temperature have a statistically significant impact on rice yield. Furthermore, weather variability, measured as standard deviations of temperature and rainfall, has a negative effect on rice yields. We use the Coupled Model Inter-comparison Project-5 outputs and dynamically downscaled the weather outputs using the regional climate model. The results of the climate model showed that the rise in temperature and disruptions in rainfall patterns including both excessive and deficient rainfall events in Tamil Nadu will continue in the future under different climate scenarios. Projected changes in the weather variables are likely to decrease rice yield in Tamil Nadu from 0.7 to 6.3% under the low emission scenario and 4.1 to 20.1% in the high emission scenario during 2022–2050 (relative to 1971–2018). These projections have implications for the planning and targeting of climate adaptation technologies such as drought-tolerant and flood-tolerant varieties to lessen the adverse impact of weather variability due to climate change in the future. [ABSTRACT FROM AUTHOR]

Any hydro-meteorology variable includes different components, in general, such as periodicity, trend, possibly jump, and uncertain stochastic parts. Among these, the trend analysis gained importance in the last three decades due to global warming and climate change effects. The literature is full of monotonic trend applications by taking into consideration trend analysis methodologies such as Mann–Kendall trend identification, Sen trend slope calculation, and Şen innovative trend analysis (ITA). It is more important in practical studies to deal with less than one-year durations to assess the possible trend pieces for better practical uses such as agricultural productivity purposes. In this paper, a new concept is applied, known as the innovative polygon trend analysis (IPTA), to assess the trend component transitions between two successive months. The application of the methodology is presented for the coastal region of northeast Algerian precipitation records. The emanated results from this study provided information that El Taref station has the most unstable precipitation behavior among all the meteorology stations in the study area, moving from a month to another rather very unsystematically; whereas other meteorology stations have systematic movement from a month to the subsequent one. [ABSTRACT FROM AUTHOR]

This paper presents a synthesis of the main characteristics of precipitation in the State of Rio de Janeiro (Brazil) based on extreme rainfall indicators. Daily precipitation data are derived from 56 rainfall stations during the second half of the twentieth century and the 2000s. Eight indices related to extreme precipitation were analyzed. The Mann–Kendall nonparametric test and the Sen's Curvature were employed to evaluate the significance and magnitude of trends. The primary climatological aspects and identified trends throughout the last decades are discussed, besides the hydrometeorological impacts associated with them. Lower values of annual total precipitation are recorded in northern Rio de Janeiro (around 800 mm) and higher in the southern State (up to 2,200 mm). The Serra do Mar affects the frequency of heavy precipitation, and the areas near the sea and high relief present the highest values of consecutive days with expressive rainfall (more than 150 mm in 5 days). These areas also showed a high concentration of flood and landslides events. Most of Rio de Janeiro exhibits precipitation intensity of about 13 mm/day. The maximum number of consecutive dry days shows a gradient from the coast (about 30 days) to the State's interior (around 50 days). Regarding trends, there is a growth of accumulated extreme precipitation in various stations near the ocean. The extreme rainfall in 24 h displays an increase in most Rio de Janeiro (+ 1 to + 5 mm/decade). The consecutive dry and rainy days present similar signs of decreasing trends, suggesting irregularly distributed precipitation in the State. This study is especially relevant for decision-makers who need detailed information in the short and long term to prevent natural hazards like floods and landslides and the related impacts in the environmental and socioeconomic sectors of the Rio de Janeiro. [ABSTRACT FROM AUTHOR]

The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth's land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted. [ABSTRACT FROM AUTHOR]

The estimation of the Intensity–Duration–Frequency (IDF) relation is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change conditions. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4). [ABSTRACT FROM AUTHOR]

The present research study aims to analyze flood frequency to relate flood magnitudes with corresponding return periods. These estimates are crucial for the development of flood-preventive hydrological infrastructures and flood plain zoning, etc. Basin-wide high intensity of rainfall and high discharge from the upper riparian region during monsoon months creates flooding in the middle and lower reaches of the Ghagra River basin. Therefore, the flood estimates for three gauging sites situated on the mainstream of the Ghagra River viz., Elginbridge, Ayodhya, and Turtipar, have been comprehended using the Gumbel distribution (Extreme Value Type I) method and the Log-Pearson Type III distribution method. Flood estimates are calculated for 1.01, 1.05, 1.11, 1.25, 2, 5, 10, 20, 50, 100, 200, and 500 years return periods considering flood time series of 50 years to reduce estimation uncertainty. The findings of flood frequency analysis (FFA) revealed that the probability of occurrence of the flood is more than 80% at all three sites because Ghagra River can carry around 7800 to 9000 m3/s of water discharge without posing a high risk of levee break. The upper and lower limits of discharge carrying capacity depend on the river's desiltation process. Hence, the flood occurs almost every year in the basin; its only variation is its severity. The rainfall-runoff relationship is estimated by integrating a simple linear model and for rainfall trend analysis Mann-Kendall is applied. Linear regression analysis-based rainfall-runoff relationship outcomes revealed a significant relationship with a positive correlation coefficient i.e., 0.2722 for Elginbridge, 0.39624 for Ayodhya, and 0.4844 for Turtipar gauging site in the monsoon season but other factors like a high amount of water discharge from dams in upper riparian regions, etc. are also responsible for flooding in the middle and lower reaches. The Mann-Kendall trend analysis shows a decrease in annual average rainfall and rainfall in the monsoon season. Discharge variability indicates the direct relationship between flood fury and changes in climatic patterns in recent decades. This paper identifies that future research is needed to better inform the policy planners who strive to design sustainable infrastructure. [ABSTRACT FROM AUTHOR]

Malaria has a significant impact on the lives of many in Ghana. It is one of the key causes of mortality and morbidity, resulting in 32.5% of outpatient visits and 48.8% of under 5-year-old hospital admissions. Future climate change may impact on this risk. This study aims at estimating the impact of climate variables and health facilities on malaria prevalence in Ghana using regional data from January 2012 to May 2017. This study links data at a regional level on malaria cases with weather data to evaluate the impact that changes in weather may have on malaria prevalence in Ghana. The results of fixed-effect modelling show that the maximum temperature has a statistically significant negative impact on malaria in the context of Ghana, and rainfall with a lag of two months has a positive statistically significant impact. Adapting to climate change in Ghana requires a better understanding of the climate-malaria relationship and this paper attempts to bridge this gap. [ABSTRACT FROM AUTHOR]

This paper has investigated the impact of convective parameterization schemes (CPS) and land surface models (LSM) on the simulation of summer climate over the Democratic People’s Republic of Korea (DPR Korea) using the regional climate model (RegCM 4.7). The sensitivity experiments with two LSMs [Biosphere Atmosphere Transfer Scheme (BATS) and Community Land Model (CLM 3.5)] and four CPSs (Grell, Emanuel, Grell over land and Emanuel over ocean (GL_EO), Emanuel over land and Grell over ocean (EL_GO)) at 30 km horizontal resolution are carried out in summer (from June to August) for 10 years (2001–2010) for this purpose. The simulation results are compared with the available observation data provided from the State Hydro-Meteorological Administration of the DPR Korea (SHMAK). The results show that summer mean circulation patterns (SMCP) and summer averaged surface temperature (SAST) is well captured for most of the simulations, but summer rainfall is not well represented by RegCM 4.7. The performance of the CLM3.5 scheme is better in all the simulations than the BATS scheme. Among the CPSs, the EL_GO scheme shows the smallest biases in the simulation of SAST and summer rainfall. The simulations using EL_GO with CLM3.5 shows the best performance in simulating the SAST and summer rainfall over the study region among the considered CPSs and LSMs. These results will be helpful to improve the prediction of climate change over the DPR Korea. [ABSTRACT FROM AUTHOR]

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of "high in the south and low in the north, high in the east and low in the west" and "high in the southeast and low in the northwest", respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change. [ABSTRACT FROM AUTHOR]

Blackgram, a protein-rich pulse crop (24%), is crucial for combating food insecurity, particularly in malnourished and economically weak countries. Enhancing blackgram production requires improved, input-saving management practices. Given the challenges of climate change and population growth, efficient water management is vital for increasing pulse productivity and water use efficiency with minimal investment. This study aimed to identify cost-effective irrigation methods to optimise blackgram yields. Experiments were conducted at the National Pulses Research Centre in Vamban, Pudukkottai, and the Agricultural College and Research Institute in Kumulur, Tiruchirappalli, during the kharif season of 2021 and 2022. The study compared different treatments of irrigation methods, such as check basin, raised bed, drip, sprinkler and rain hose irrigation. Results showed that the rain hose system maintained the highest soil moisture (23.93% at 10 cm depth and 19.71% at 20 cm depth). Even though drip irrigation resulted in a higher seed yield (1363 kg ha−1), the rain hose system proved to be more cost-effective, saving 27.09% in costs and achieving a 15.23% higher benefit–cost ratio. These findings suggest that the rain hose method, combined with current agronomic practices, is a viable low-cost technique for sustainable blackgram cultivation, optimising water use and maximising profits. This research provides valuable insights into water-saving irrigation methods for pulse crops. [ABSTRACT FROM AUTHOR]

This research aimed to assess changes in mean and extreme rainfall within the Kaduna River Basin (KRB), specifically examining the implications of two Representative Concentration Pathways (RCPs)—4.5 and 8.5 scenarios. Employing a quantile mapping technique, this study corrected inherent biases in four Regional Climate Models, enabling the examination of mean precipitation and six indices capturing extreme precipitation events for the 2050s. These findings were compared against a historical reference period spanning from 1981 to 2010, considering the basin's upstream and downstream segments. Results revealed an average annual rainfall reduction under scenarios 4.5 (21.39%) and 8.5 (20.51%) across the basin. This decline exhibited a more pronounced impact on monthly rainfall during the wet season (April to October) compared to the dry season (November to March). Notably, a substantial decrement in wet indices, excluding consecutive wet days (CWD), was foreseen in both seasons for the upstream and downstream areas, signalling an impending drier climate. The anticipated rise in consecutive dry days (CDD) is poised to manifest prominently downstream attributed to global warming-induced climate change brought on by increased anthropogenic emissions of greenhouse gases. These findings accentuate a heterogeneous distribution of extreme rainfall, potentially leading to water scarcity issues throughout the KRB, especially impacting upstream users. Moreover, the projections hint at an increased risk of flash floods during intense wet periods. Consequently, this study advocates the implementation of targeted disaster risk management strategies within the KRB to address these foreseeable challenges. [ABSTRACT FROM AUTHOR]

Devising effective strategies to retard the negative impacts of extreme climatic events on water security in general and environmental water balance in specific is imperative, especially in semi-arid rural-Western-India, where climate change has markedly increased water scarcity in domestic and agricultural sectors. This exploratory research thus aimed at investigating the water budget against mismanagement of available water resources for remote-marginalized villages in rural-Nashik (West-India). Investigation entailed visual interpretation of LULC analysis (2008–2017) using fine-scale Google Earth imageries, rainfall-runoff analysis using SCS-CN method, determining the supply-demand potential of water storage structures using field-experimentations and PRA tools, and estimation of season-wise water-budget using hydrological (water-balance) equations. Results identified agriculture as the major land-use (~ 78%) followed by hilly regions (~ 16%) and water bodies (~ 3%). Surface runoff was found as the dominating hydrological phenomenon (33–89% of monsoonal rainfall) followed by surface storage (6–36% of annual rainfall) and groundwater flow (4–82% of annual rainfall). Deforestation over hills for firewood, which reduced forest cover by 52%, was observed as the primary concern for soil erosion, thereby siltation of water bodies and higher runoff against percolation. Erratic rainfall patterns (departure range − 42 to 83% during 1998–2017) coupled with sub-graded irrigational systems confined the agricultural practices to one season [South–West monsoon (June–September)]. High unmet drinking water demand (73% to 98%) forced women communities to fetch water by walking 4.5 ± 1.5 km. Considering the urgent response to collectively combat water-budget imbalance, integrated water security plans were proposed using decentralized participatory watershed development approaches. [ABSTRACT FROM AUTHOR]

Bangladesh is a highly climate vulnerable region. Among the many areas of Bangladesh, the haor region is considered as one of the most climate change sensitive areas. Again, the nation greatly depends on the agricultural produce of the haor area. So, adoption to climate change strategies is vital for the farming community of Bangladesh. The current study was conducted based on the idea of understanding the depth of knowledge of farmers regarding climate change, identifying the currently practiced climate change adaptation strategies and to know the influential factors behind the adoption of those practices. The study was drawn on primary data collected from 300 farmers of the Dingapota haor of Mohanganj upazila under Netrokona district of Bangladesh through a structured interview schedule. Descriptive analysis, adaptation Strategy Index (ASI), and Pearson's product correlation coefficient (r) were used to analyze data with the help of Excel and SPSS. The study found that the intensity of flash floods, short winter seasons, and unpredictable rainfall have significantly increased. Most respondents believe that certain parts of the climatic conditions are getting worse. Farmers' knowledge about crop diversification secured first and floating agriculture secured second position in case of advanced proficiency to cope with climate change vulnerability. The research exposed that changes in planting and harvesting dates are the most efficient climate change adaptation strategy practiced by farmers and their experience of agricultural farming strongly influences adaptation choices in the study area. [ABSTRACT FROM AUTHOR]

The increasing concentrations of greenhouse gas emissions in the atmosphere along with the increasing temperatures exacerbate the situation, making it one of the major issues for food security. This research aims to explore the effects of climate change on food production in India. More specifically, this study investigates the impact of temperature, rainfall, CO2, methane, and N2O emissions and energy use on food production using a time spanning from 1990 to 2019 and explores the major critical factors impacting food production in India. The study used autoregressive distributed (ARDL) estimates for long-run and short-run cointegration. The empirical results demonstrated that energy use, rainfall, and methane emissions improve food productivity, whereas temperature and N2O emissions undermine food production in the long run and short run. However, the results revealed that CO2 emissions do not affect food production. Additionally, we used the dynamic ordinal least squared approach to verify the robustness of ARDL results. The results also demonstrate that N2O emissions and temperature are critical determinants of food production, indicating that a rise in temperature and N2O emissions significantly reduces food production in India. On the other hand, the findings show that methane emissions and rainfall significantly increase food production with a coefficient of 0.19 and 0.059, respectively. The most important adaptation strategies that should be considered due to climate change are reducing greenhouse gas emissions, expanding renewable energy investment, and adopting new technologies to combat environmental challenges. [ABSTRACT FROM AUTHOR]

Understanding divergent perceptions of ethnic groups to climate change in mountainous regions home to multi-ethnic cultures and the factors influencing these perceptions is crucial for policymakers to predict the trending impacts of climate change and make long-term decisions. Based on the case of Southwest China, 1216 households were interviewed by questionnaire surveys to gain insight into the perceptions of local people on the dynamic evolution characteristics of climate events in the uplands of Yunnan, China, which is an area home to rich ethnic diversity, and also to determine the factors that influence these perceptions. Results indicated that climate events have now become important events for farmers' livelihoods, ranking only after family diseases and livestock diseases. Drought, long-term drought, and erratic rainfall are the three kinds of climatic events with the most significant increase in frequency and severity in mountainous areas. Farmers' perceptions on whether drought, long-term drought, and erratic rainfall occurred 10 years ago as well as changes in frequency and severity are significantly influenced by characteristics of respondents, ethnic culture, geographical environment of farmer residences, farmland characteristics, and sources of livelihood. Ultimately, taking ethnic differences into consideration for long-term planning will be an important part of the local response to climate change in the future. [ABSTRACT FROM AUTHOR]

The quest to eradicate poverty, central to the United Nations Sustainable Development Goals (SDGs), poses a significant global challenge. Advancement in sustainable rural development is critical to this effort, requiring the seamless integration of environmental, economic, and governmental elements. Previous research often omits the complex interactions among these factors. Addressing this gap, this study evaluates sustainable rural development in China by examining the interconnection between agricultural production and government-led poverty reduction, with annual rainfall considered an influential factor of climate change impacts on these sectors and overall sustainability. Utilizing a Meta-frontier entropy network dynamic Directional Distance Function (DDF) within an exogenous Data Envelopment Analysis (DEA) model, we categorize China's 27 provinces into southern and northern regions according to the Qinling-Huaihe line for a comparative study of environmental, economic, and governmental efficiency. This innovative approach overcomes the limitations of previous static analyses. The findings reveal: (1) Rainfall, as an exogenous variable, significantly affects agricultural production efficiency. (2) The overall efficiency in both southern and northern regions increases when accounting for rainfall. (3) Government effectiveness in poverty reduction is comparatively lower in the northern region than in the southern region when rainfall is considered. These insights underscore the importance of including climatic variables in sustainable development policies and emphasize the need for region-specific strategies to bolster resilience against climatic challenges. [ABSTRACT FROM AUTHOR]

Emerging large ensemble climate datasets produced by multiple general circulation models and their downscaling products challenge the limits of hydrodynamic models because of the immense data size. To overcome this new challenge and estimate the discharge quantiles corresponding to different return periods at all river sections in an entire region, this study proposes an event-based regional approach that uses a nationwide distributed rainfall–runoff model as well as large climate projection ensembles. This approach addresses the high computational burden associated with continuous simulations and solves the problem of conventional event-based simulations serving only a single outlet of a basin. For our analysis, we extracted 372 annual maximum 48 h rainfall events that cover the entirety of Shikoku Island and its eight major river basins. Peak discharges were estimated using a 150 m resolution rainfall–runoff–inundation model. These discharges were then screened using either the peak-over-threshold (POT) method or block maxima (BM) method, and frequency curves were subsequently constructed and evaluated. The primary reason for the necessity of POT or BM was to avoid interference from extraneous low discharges. The POT-based frequency curves showed good accuracy when using peak discharges in the range of the top 10–50%, and the results remain stable within this threshold range. The BM method, employing block sizes of 2–5 years, can generate relatively accurate frequency curves, but the choice of block size introduces significant variations in results among certain basins. Generally, the accuracy of results based on the POT method surpasses that of the BM method. Considering the accuracy, computational cost, and result stability, the POT method is preferred. The error introduced by the regional approach was acceptable with more than half of the relative root-mean-square errors remaining within 10% and basically all of the results are within 20%. The results of the regional approach exhibited good accuracy across climate scenarios and provided consistent information regarding future flood quantiles. This study serves as the foundation for high-resolution future flood risk assessment. [ABSTRACT FROM AUTHOR]

Climate change is affecting the global hydrological cycle, causing drastic changes in precipitation patterns. Extreme climatic events are becoming more frequent and intense than in the past, leading to water-level fluctuations and affecting aquatic ecosystems. Semiarid regions are very susceptible to changing climate. We analyzed a 10 years dataset from a tropical semiarid reservoir during extreme hydrological events (heavy rains and prolonged drought), and evaluated phytoplankton functional responses to environmental conditions. We found, as hypothesized, that phytoplankton functional structure change in a temporal scale due to water–volume fluctuation induced by the rainfall pattern. Depth and inorganic material acted as environmental filters selecting phytoplankton groups. High water level seems to improve water quality and low water level worsen it. Colonial and filamentous cyanobacteria dominate the wet period; however, it may have a critical threshold during severe periods of drought, which will lead to dominance of groups well adapted to low light conditions and with mixotrophic metabolism. Phytoplankton functional approaches can simplify phytoplankton identification and reflect better the environmental conditions than the taxonomic approach. Therefore, these approaches can help to understand the shifts in aquatic ecosystems under extreme hydrological events and predict functional response of phytoplankton being an important tool to water management and conservation. [ABSTRACT FROM AUTHOR]

Background: Treeline ecotones of Mediterranean ecoregions have been affected by the increasing intensity and severity of droughts. Even though the effect of droughts on forest dynamics has been widely documented, knowledge is relatively scarce of how extreme climate episodes affect the hydraulic structure and, therefore, the physiology of woody plants. The Mediterranean Andes have experienced an uninterrupted period of drought since 2010, including an extremely dry year in 2019 with approximately 80% rainfall deficit. Here, we investigated shifts in wood anatomical and physiological traits of Kageneckia angustifolia, an endemic treeline species, in response to this drought period. Methods: We evaluated the xylem plasticity of three K. angustifolia populations across their natural distribution (31–35° SL) based on anatomical (vessel structure and distribution) and physiological (intrinsic water-use efficiency) variables in the tree rings. We focused on the period 2000–2020 that corresponds to before the megadrought (2000–2007), (ii) megadrought (2008–2018) and (iii) hyperdrought (2019–2020). The variables were annualized and analyzed by linear mixed-effects models. Results: Our results provide insights to the anatomical and physiological mechanisms underlying the resilience of treeline forests to persistent droughts in central Chile. We found that the extreme drought in 2019–2020 triggered shifts in vessel size and frequency that increased hydraulic safety. These significant shifts in vessel traits occurred in parallel with a decrease in pit aperture area and an increase in water-use efficiency, further increasing the resilience of K. angustifolia to extreme drought stress. Conclusions: Our results revealed coordinated shifts in vessel size and frequency and water-use efficiency in response to the megadrought, thereby reducing vulnerability to hydraulic failure. The apparent resilience of K. angustifolia to extreme droughts suggests that this adaptation to drought stress may increase its ability to tolerate novel climatic conditions of treeline environments of the Mediterranean Andes, although it is not clear whether these adaptations will be sufficient to persist in scenarios that predict intensification of climate stress. Finally, our results provide empirical evidence that integrating wood anatomical and physiological traits facilitates the understanding of resilience mechanisms that treeline forests develop in the face of increasing drought stress. [ABSTRACT FROM AUTHOR]

Investigating the temporal dynamics of rainfall in a changing climate, especially in rainfed agriculture regions, is crucial for analyzing climate-induced changes and offering adaptation options. Since Mizoram experiences unfavorable impacts of rain nearly every year, the region rainfall has been altering over the years, and vital climatic activity is becoming uncontrollable. The current study is primarily concerned with the changing trend of rainfall over Mizoram, which includes both short-term persistence (STP) and long-term persistence (LTP) of rainfall in seasonal and annual time series of rainfall overseeing for the period of 25 years of daily average rainfall from 1996 to 2020 collected collectively from the seven stations over the study area of Mizoram. Four different Mann-Kendall method iterations were used to analyze rainfall trends: the original or conventional method (without autocorrelation) (MnKn1), removing lag-1 autocorrelation (trend-free pre-whitening), considering multiple lag autocorrelation (more than lag-1 autocorrelation) (MnKn3), and Hurst coefficient or LTP (MnKn4). In the analysis, the study found that during monsoon, station Lawngtlai (LT) observed the highest rainfall having a Z value of 1.986, increased by 0.466 cm/year, while station Serchhip (SC) observed the lowest rainfall having Z value of −2.282, decreased by −0.163 cm/year. After applying modified MnKn4, we observed LTP of rainfall in winter at station Lawngtlai (LT) with an increasing trend and other stations observing STP in almost all seasons either increasing or decreasing trend. Therefore, possible climate change adaptation measures should be made to optimize rainfall use for various applications for the states of Mizoram. [ABSTRACT FROM AUTHOR]

Rising temperatures of 1.5–4 °C by the end of the twenty-first century and continuing after 2100 have caused climate change to threaten food security. Indeed, the rainfed production of strategic crops such as wheat in countries such as Iran, which are likely to be highly affected by climate change, is very important. This study aimed to identify the suitable areas for rainfed wheat cultivation and the yield gap estimation in current and future climatic conditions using geographical analysis, a crop simulation model, and the GYGA protocol in Iran. For this, environmental variables (including average, minimum, and maximum temperatures, rainfall) along with topographic (slope, elevation) and edaphic components (such as organic carbon, pH, EC, [CaCO3], exchangeable sodium percentage, cation exchange capacity, and soil erosion) were involved. The results revealed that around 30% of the total areas (6.62 million ha) are not suitable at all, while just 13% of total lands (2.97 million ha) were highly suitable and suitable. These areas are mainly located in the northern part of Iran. The study of the climate change scenarios indicated that the northern, northwestern, and western parts of the country have great potential for rainfed wheat production and future climate change will benefit wheat production in these areas, but in other parts of the country, more unfavorable conditions are expected. The mean water-limited potential yield (Yw) difference between marginally suitable to not suitable classes was narrow (< 0.3 t ha−1), while for highly suitable to moderately suitable classes was about 2.5 t ha−1. [ABSTRACT FROM AUTHOR]

This study examines gender vulnerabilities and responsive strategies to climate change, comparing evidences from Kwara and Nassarawa States in Nigeria. Changes in climate parameters, gender-based perceptions of climate, as well as gender-based response and adaptation practices were assessed in accordance with specific research objectives. A total of 200 participants were surveyed through a mixed method approach using 41 years of climate data. Semi-structured questionnaires were administered equally in the two States and 52 in-depth interviews were conducted within male and female farmers that were 40 years and above age using a purposive sampling method. Results from Nassarawa State showed a downward trend in rainfall and an upward trend in both minimum and maximum temperatures. The farmers perceived climate change differently, with observed changes in climate variables: temperature and precipitation, resulting in extreme floods, drought, and rainfall onset and leading to varying adaptation practices. The study concluded that gender plays a significant role in the adoption of adaptation practices in the agricultural sector and that males often have more access to resources and decision-making power in farming as the heads of households. There is a need for better gender-sensitive approaches to adaptation planning and implementation to ensure that both men and women have equal opportunities to benefit from adaptation options in agriculture. [ABSTRACT FROM AUTHOR]

Although the ecological and economic services rendered by the wetland ecosystems are innumerable, the exposure of inhabitants to hazardous climatic events is on the rise. For instance, the Kuttanad wetland ecosystem in Kerala, India, faces uneven rainfall patterns, leading to recurrent flooding. The present study examines people's vulnerability to elevated flooding risk in the region, factors responsible for migration in the wake of climate change and their adaptive capacity to such events. The primary survey-based study follows the theoretical framework of vulnerability and adaptive capacity. Physical asset loss, sinking houses, elevated health risks and loss of livelihood are factors identified for increased vulnerability to flood risks. The exacerbating vulnerability translates into the mass migration of local inhabitants. The Probit regression underscores the role of households' socio-economic background in migrating from the region, seeking safe havens. Marginalised social groups and people reliant on the local environment are most vulnerable. As per the study, the absence of pre and post-flood measures affects the adaptive capacity of the inhabitants. Given the gravity of flooding risk, the study suggests channelised policy measures that are quintessential to improve their resilience and adaptive capacity. [ABSTRACT FROM AUTHOR]

Climate change is expected to have serious socioeconomic impacts on smallholder agriculture, but overall impacts will also depend on the extent of household adaptation to climate change. This study investigates household-level factors that may help describe and explain perceptions about climate change and examine how these perceptions influence choices related to specific land-use adoption strategies. Logistic regressions were applied to address these objectives. Cross-sectional survey data were derived from 315 randomly selected smallholder mixed farmers in Ethiopia. The results indicate that a significant number of farmers believe that temperatures have increased over the last 10–20 years and that precipitation has declined. Education, agroecological settings, and social capital significantly influenced perceptions of increased temperature. Gender, distance, access to climate change information, and social capital significantly influenced perceptions of reduced rainfall. The odds of decisions to adopt specific land-use adaptation measures to climate change are significantly influenced by perceived changes in rainfall and temperature but also by social, human, and natural capital access. Adoption is also linked to gender, distance to markets, access to climate change information, and farm location. Thus, rural interventions aimed at addressing more general agricultural adaptation to climate change should account for these factors. [ABSTRACT FROM AUTHOR]

Rainfall variability is a key element in water resource management. There has been significant variability in rainfall in Arunachal Pradesh, with the state being in the highest rainfall zone in India. The present study attempts to investigate the annual rainfall trend along with the change points in the rainfall time series, considering more than a hundred years of data (1901–2002) in eleven districts of Arunachal Pradesh. First, a serial correlation test was conducted on the entire time-series data for the three districts to detect the serially independent time series, followed by the non-parametric Mann–Kendall test and Spearman's rank correlation test to ascertain the presence of a statistically significant trend in hydrological climate variables. Sen's slope method was applied to estimate the magnitude of the trend. Pre-whitening, trend free pre-whitening Mann–Kendall, and bias corrected pre-whitening, along with two variance correction approaches, are applied to the serially correlated data. All the districts under consideration show a decreasing trend in rainfall in the investigation over the years. A comparative study of the trend test method was also carried out. Further, to identify the trend change points in the time series, a sequential Mann–Kendall test is conducted. Assessing 100 years of time series data for the region makes the study unique of its kind and is likely to play a vital role in environmental policymaking. Furthermore, it will be helpful for water resource management, land use, land cover management, sustainable agricultural planning, and the overall socio-economic development of the region. [ABSTRACT FROM AUTHOR]

Meteorological disasters have increasingly become one of the important interferences limiting vegetation growth and productivity recent years, especially in ecologically fragile regions. However, it is unknown how much the impact of meteorological disaster on the vegetation in ecologically fragile area under the changing climate. This study aims to identify the spatial and temporal distribution of four meteorological disasters (drought, rainstorm, high temperature, and low temperature) as well as net primary productivity (NPP) reduction rate in Guangxi province, China, which has large ecologically fragile Karst areas. We also aim to quantify the relative impact of each disaster on NPP loss. During the last 20 years (2000–2019), there was a decreasing trend for drought indicator (drought days), but an increasing trend for rainstorm (cumulated rainfall for daily rainfall higher than 50 mm and less than 99.9 mm), high temperature (daily maximum air temperature higher than 35°C and less than 37°C days), and low temperature (cumulated thermal time for daily minimum temperature less than 0°C) indictors. In the northeast area of study region, all the intensity of rainstorm, high- and low-temperature disasters showed an increasing trend. Under the more intense and frequent meteorological disasters, 87% study sites (60 stations/69 stations in total) showed an increasing trend in terms of NPP reduction rate. Results on grey correlation between each meteorological disaster and NPP reduction rate showed that high-temperature disaster had the greatest impact (27%) on vegetation growth, followed by drought (25%) and rainstorm (25%) disaster, and then low-temperature (23%) disaster. Our results would be helpful for meteorological disasters warning, vegetation protecting as well as policies making for governments. [ABSTRACT FROM AUTHOR]

This work simulates rainfall using the GFDL-ESM2G large-scale model (from the Intergovernmental Panel on Climate Change-Fifth Assessment Report (IPCC-AR5)) and the change-factor method to downscale rainfall under three emission scenarios: RCP 2.6, RCP 4.5, and RCP 8.5. The Storm Water Management Model (SWMM) is applied to simulate stormwater driven by rainfall inputs in zones 1 and 3 of the northeastern municipality of Tehran under baseline (1988–2005), near-future (2030–2047), and far-future (2048–2065) conditions. The results indicate that the rainfall intensity for the design event with a 50-year return period would increase in the near future (2030–2047) and far future (2048–2065). Deployment of four types of low-impact development (LID) stormwater control measures (SCMs), i.e., vegetative swales, bio-retention cells, permeable pavement, and infiltration trenches for urban stormwater control in the study area, shows that there would be a significant change between the "with LID SCMs" condition and the "without LID SCMs" condition with respect to the flood volume at the basin outlet. The LID SCMs would reduce the flood volume in the near future by 22%, 23%, and 21% under the RCP2.6, RCP4.5, and RCP8.5, respectively, and they would reduce the flood volume in the far future by 23%, 27%, and 23% under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. [ABSTRACT FROM AUTHOR]

Afghanistan, as a landlocked country located within central and southwestern Asia, has an arid to semi-arid climate. Most of the people are involved in agricultural activities, and a major part of the country's gross domestic product depends on agriculture, but the country has the lowest water storage capacity. Consecutive periods of drought and rapid snowmelt due to climate change have made it more challenging for suitable water resource management practices. This study investigates the historical meteorological drought characteristics across the whole country by employing the Reconnaissance Drought Index for the period 1979–2019 using data from 55 meteorological stations. Trends in precipitation and temperature are also investigated using the Mann-Kendall's and the Sen's slope statistical tests. A four-decadal countrywide drought map is generated. Extreme and severe droughts were observed in 1999 and 2000 across the whole country. Moderate drought events have started to occur with a frequency of 3 to 5 years since 1999. The decadal annual rainfall values in each river basin indicate that rainfall has decreased in the last two decades with a significant decline in 1999-2008. The trends of increase in temperature and decrease in precipitation are indications of rapid climate change in the country, especially in the south, west, and southwest regions. Due to the intensity and frequency of the droughts, river flow rates have decreased; and therefore, there is a need for the upstream and downstream neighboring countries to come to terms with the phenomenon of a new normal in the hydrological cycle and accordingly revise new water sharing treaties. [ABSTRACT FROM AUTHOR]