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Copyright of Ingeniería Solidaria is the property of Universidad Cooperativa de Colombia 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.)

Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters. [ABSTRACT FROM AUTHOR]

The occurrence of harmful algal blooms (HABs) in coastal and inland waters has a significant impact on societies. This complex biogeophysical phenomenon becomes further complicated due to the impact of climate change. This review summarizes the research performed in recent years in the direction of climate change on three lake parameters, viz. lake temperature, precipitation, runoff, and lake ice, which impacts the lake ecology and, in turn, impacts the HABs. The present paper also reviews the research work related to the relationship between climate change and HABs. The purpose of this study is to provide the researchers with the opportunity to understand the current research in the direction of climate change and HABs so they can contribute effectively to one of the most important phenomena that will severely impact water quality in the future warmer climate, in coastal as well as inland water bodies. Furthermore, this work aims to discuss how HABs will change in the future warmer climate. [ABSTRACT FROM AUTHOR]

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. [ABSTRACT FROM AUTHOR]

The subject of the research paper is the use of remote sensing in monitoring and analyzing the impact of climate change on the occurrence of extreme precipitation, and the causeand-effect occurrence of floods in the area of the Sana River Basin in Bosnia and Herzegovina. The goal is to process the "product" of remote sensing to identify the time intervals of occurrence of extreme precipitation, to assess their impact on water levels, and to map potential floods in space. Spatial identification of zones that are at risk of flooding is an integral part of the aforementioned goal. Precipitation monitoring was performed by processing Climate Hazards Group InfraRed Precipitation with Station Data through the Google Earth Engine platform. The observed 30-year period (1992-2022) was compared with the average precipitation for 2017, 2018 and 2019. The impact of extreme precipitation on the water level of the Sana River was analyzed. Flooding periods have been identified: February and December 2017, March 2018 and May 2019. Mapping of flooded areas was carried out by pre-processing and post-processing of Sentinel-1 radar satellite images. The total flooded area is: 710.38 ha (February 2017), 496.79 ha (December 2017), 417.86 ha (March 2018) and 422.42 ha (May 2019). Based on the identified flooded areas, a flood risk map was created on the main course of the Sana River. The research contributes to a better understanding of the changes that occur in the area under the influence of climate change, and the data presented are important for numerous practical issues in the field of water resource management and flood protection. [ABSTRACT FROM AUTHOR]

In the context of anomalous global climate change and the frequent occurrence of droughts and floods, studying trends in the conversion rate between precipitable water vapor (PWV) and actual precipitation in a certain region can help in analyzing the causes of these natural disasters. This paper examines the variation trend in the conversion rate between PWV and actual precipitation on a monthly scale in Hubei from 1960 to 2020. To estimate historical PWV data, we propose a new method for estimating PWV using water vapor pressure based on the RF algorithm. The new method was evaluated by radiosonde data and improved the accuracy by 1 mm over the traditional method in Hubei. Based on this method, we extrapolate the monthly average PWV in Hubei from 1960 to 2020 and analyze the conversion rate between PWV and precipitation during this period. Our results showed that there was no obvious cyclical pattern in the conversion rate in either the longitude or latitude directions. In Hubei, where the topography varies significantly in the longitude direction, the conversion rate is influenced by topography, with the smallest conversion rate being in the transition zone between the mountainous region of western Hubei and the Jianghan Plain. In the latitudinal direction, the conversion rate decreases with increasing latitude. [ABSTRACT FROM AUTHOR]

The high variability of the sub-desert climate, especially in the south-eastern region of Morocco, has severe socioeconomic impacts on the inhabitant's way of life, as is the case in the Daoura watershed, where this variability is associated with droughts or exceptional rainfall. The data collected from the Guir-Ziz-Rheriss hydraulic agency were processed, corrected and analyzed using the Climatol package (version 4.0.0) developed in R software to homogenize rainfall data. Through this work, the significance and amplitudes of annual and monthly rainfall trends were defined using the Mann-Kendall test and Sens's slope estimator, while comparing the results of raw and homogenized data. The Daoura watershed has a sub-desert climate, and the homogenization process revealed a few rainfall stations with significant positive trends at confidence levels ranging from 90% to 95%. According to the raw and homogenized data, the majority of these stations are located in the High Atlas (CR1) and Anti-Atlasic (CR2) zones, where there is considerable spatiotemporal variability in rainfall from one year to the next. The essential objective of this scientific paper was to analyze the spatiotemporal variability of monthly and annual precipitation and to study their trends through rainfall data homogenized by the climatol package (version 4.0.0) from 13 stations over a period (1957-2018). The contribution of this study to science is the rainfall data it offers, which is useful for managing natural resources in sub-desert areas. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office 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.)

Especially in recent years, the study of landslide phenomena is considered as very important because of the effects of climate change. The aim of this paper is to examine the stability of the slope located in Miacher Nagar village along the Hunza River (HR), using the Limit Equilibrium Method (LEM). The Miacher slope rises to a height of 900 m from the foot of the Hunza River and has a base angle of 50 degrees. Meta-sediments and quaternary recent glaciated deposits make up the majority of the slope's composition. The slope movement of Miacher was first triggered in 1995, and was further triggered in 2010 and 2013. The slope was geologically, geomorphologically, geotechnically and geochemically investigated as well as modeled by Slope/w to determine the safety factor. Soil samples were analyzed for their geotechnical, geological and geomorphological properties. The Limit Equilibrium Method (LEM) was employed in this study to analyze the Factor of Safety (FOS) of the slope, based on assumptions of the Morgenstern and Price, Ordinary, Janbu and Bishop Methods, using the Slope/w software. Various factors, including pore water pressure, unit weight, cohesion, angle of internal friction and overburden, were examined by analyzing different scenarios. The findings showed that an increase in cohesion and angle of internal friction resulted in an increase in FOS, whereas an increase in unit weight and overburden caused a decrease in FOS. The influence of pore water pressure was positive to a certain extent, but a further increase led to a significant reduction in FOS. The results showed that the Miacher slope is currently stable, as all FOS values were greater than one, based on the existing strength parameters and simulated results obtained using Slope/w. [ABSTRACT FROM AUTHOR]

Climate change is one of the most pressing issues of our time. Rising temperatures, changing precipitation and more weather extremes pose risks to local societies worldwide. Yet, climate change is most often presented and reported on a global or national scale. This paper aims to analyze the key aspects of climate change on the local scale by assessing temporal and spatial changes in temperature and precipitation in the Westfjords in north-western Iceland and evaluate their impacts on the region's livability. Existing temperature and precipitation data were used to model trends in climate change at an unprecedented resolution. The results show that the period of 2001–2020 was warmer than the 1961–1990 reference period in almost every month of every year, and that warming was more pronounced in the winter months. Furthermore, precipitation increased during 1991–2020 period compared to 1961–1990. These detected local patterns confirm some of the major predictions about climate change on the global scale. Considering the impact of climate change at the local level is critical, as it allows the community to envisage their future and provides better possibilities to mitigate, prepare for or adapt to the predicted changes. [ABSTRACT FROM AUTHOR]

The Grain for Green Project (GGP) has considerably improved the vegetation cover of the Loess Plateau, as well as changed the carbon and water coupling process of local vegetation to a certain extent. Water use efficiency (WUE) is a crucial measure for evaluating ecosystem responses to global climate change and is a key indicator of the carbon–water coupling between terrestrial ecosystems and the environment. A comprehensive understanding of the impact of vegetation reconstruction on WUE on the Loess Plateau is of great significance to the vegetation growth and contribution to sustainable of the Loess Plateau. In recent years, scholars have gained a more comprehensive understanding of the distribution and drivers of WUE on the Loess Plateau. However, through the study of carbon and water coupling in the Loess Plateau, it is found that the effects of different vegetation restoration levels on WUE are still to be studied in depth in terms of spatial and temporal heterogeneity and long timeseries. In this paper, we analyzed the trends of Normalized Difference vegetation cover (NDVI) and WUE from 2001 to 2010 and 2011 to 2020, respectively, to research at the WUE of the vegetation in this area in relation to vegetation restoration. It was found that the Loess Plateau's vegetation WUE rose from 2001 to 2020 at a rate of 0.023 g C kg−1 H2O per year, and that the increase from 2011 to 2020 was more significant than the growth from 2000 to 2010. The Loess Plateau's area with a growing trend in vegetation water use rate increased from 77.12% in 2001–2010 to 88.63% in 2011–2020, with the majority of the increased area occurring in the northeastern Inner Mongolia region. After 20 years of the reforestation project, the area where NDVI and WUE increased simultaneously accounted for 71.54% of the Loess Plateau, the area where NDVI increased but WUE decreased accounted for 10.95% of the Loess Plateau, and the area where NDVI increased but WUE decreased accounted for 7.15% of the Loess Plateau. The correlation between temperature precipitation and WUE was not significant for the whole Loess Plateau, further indicating that the increase in vegetation cover was the main reason for the increase in vegetation water efficiency. Therefore, the effect of vegetation cover on WUE should be fully considered when vegetation restoration is carried out on the Loess Plateau. [ABSTRACT FROM AUTHOR]

In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen's slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the flood formation module in the Trotuș river basin and especially on its tributaries. A special situation was recorded in 2004 when the floods formed on the tributaries presented very high flows, but which did not substantially influence the flow of the main course. The floods produced on the river / stream / torrent type tributaries (example: Asău, Agăț, Goioasa, Iedera) presented flows that exceeded the accepted calculation probabilities. The floods produced were both the effect of torrential rainfall and the configuration of the lower sectors of the riverbeds. The floods produced in 2004 on a series of tributaries of the Trotuș River presented maximum flows that exceeded the calculation probabilities of 0.1% (Agăț - 183 m3/s, Beheghet - 50.70 m3/s, Goioasa - 67.10 m3/s, Iedera - 127 m3/s). The sudden change of the slope on the lower course of the tributaries determined the deposition of a large volume of alluvium, a situation that reduced the flow section and even blocked it. The result of the corroboration of natural and anthropogenic situations in the propagation of these floods is evidenced by the great destruction produced in a territorial area with numerous human communities and important economic activities. [ABSTRACT FROM AUTHOR]

The data set represents the Regional Meteoric Water Line (RMWL) for the Yucatan Peninsula (Mexico), a region with karstic aquifers but little knowledge of the isotopic composition of meteoric water. This data paper comprises the isotopic composition of meteoric water collected from November 2018 to November 2019 as monthly composite samples expressed as weighted monthly mean precipitation from 16 locations across the Yucatan Peninsula. The RMWL was δ2H = 7.803 δ18O + 12.075, with a slope and intercept suggesting precipitation from air that has undergone condensation, air masses with variable moisture or recycled moisture. The average δ18O is −2.57‰ (−12.23 to 1.2‰) and δ2H is −7.94‰ (−83.39 to 18.32‰). This data set was collected by the implementation of an isotopic monitoring network, gathering information useful as a tool for better understanding of the hydrology and hydrogeochemistry of karstic aquifers, and to develop proxies for paleohydrology, ecohydrology, climate change and paleoclimate studies in the Gulf of Mexico and the Great Caribbean Area. [ABSTRACT FROM AUTHOR]

In this paper, a method was developed in relation to the north-western coast of the Black Sea in order to determine the optimal model run from regional climate models ensemble. As a result of climate change, which has been observed since the late 1980s in Ukraine, various natural objects changes have been also transformed. The study of such changes in the future is possible only by using runs of global or regional climate models. Moreover, the step of the spatial grid in the climate model must be comparative with the spatial size of a natural object under study. In the north-western coast of the Black Sea, climate change is characterized by increasing aridity of climate and a corresponding decrease in freshwater inflows into coastal lagoons from their catchments, making ecosystems of these lagoons sensitive and vulnerable to climate change. Using numerical models in order to study climate change impact on these natural objects requires input hydrometeorological information in the spatial grid points, the distance between which should correspond to the horizontal size of lagoons, i.e. several kilometers. In this paper, data from the scenarios RCP4.5 and RCP8.5 of the ensemble from 14 model runs with different regional climatic models of the CORDEX project were used to simulate the future changes of the temperature and precipitation regime. For each grid point and scenario, a single simulation was selected from the ensemble, which best reproduces the intra-annual changes of temperature, precipitation, and evaporation compared to the ensemble means. Despite the sufficiently large distance between the estuaries, the method allowed the selection of a single optimal model run, which shows the significant differences in spring and summer precipitation as well as year-around evaporation in the southern and northern parts of the northwestern coast of the region. This run well reproduces the relationship between temperature, precipitation, and evaporation in the southern and northern parts of the northwestern coast of the Black Sea.

Global climate change is considered one of the greatest environmental threats in the world. It is expected to significantly change the global hydrological cycle. The two main water cycle components, potential evapotranspiration (PET) and precipitation (P), are closely related to vegetation dynamics. In this study, the partial correlation analysis method was used to analyzed the relationship between Normalized Difference Vegetation Index (NDVI) and climate factors (PET and P) based on grid cells. PET was calculated by FAO-56 Penman-Monteith method. Moreover, we also investigated the NDVI and climate factors in different vegetation cover types. The results showed that grassland, forest and cropland in China were positively correlated with PET and P. The time scales of the maximum partial correlation coefficients between NDVI and PET of grassland vegetation were mostly longer than 5-6 months. These time scales were longer than the time scales related to P. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China, whereas the spatial distribution of related time scales was the opposite. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China. However, the spatial distribution of related time scales was the opposite. The correlations between NDVI and PET, P of cropland vegetation and the time scales related to PET had clear spatial heterogeneity. The time scale of the correlation between NDVI and P for cropland in the northern China was about 2 months. P had a strong influence on the growth of various types of vegetation in the study area, and grassland vegetation was affected by P over the shortest time scale. We compare and analyze the results of this study with other related studies. These results provide a reference for exploring the dynamic changes in different vegetation types and factors impacting them. [ABSTRACT FROM AUTHOR]

Analyzing long-term climate changes is a prerequisite for identifying hotspot areas and developing site-specific adaptation measures. The current study focuses on assessing changes in precipitation, maximum and minimum temperatures, and potential evapotranspiration in Zambia and Malawi from 1981 to 2021. High-resolution precipitation and temperature datasets are used, namely, Climate Hazards Group InfraRed Precipitation with Station data (0.05°) and Multi-Source Weather (0.1°). The Mann–Kendall trend test and Sen's Slope methods are employed to assess the changes. The trend analysis shows a non-significant increase in annual precipitation in many parts of Zambia and Central Malawi. In Zambia and Malawi, the average annual and seasonal maximum and minimum temperatures show a statistically significant increasing trend (up to 0.6 °C/decade). The change in precipitation during the major rainy seasons (December–April) shows a non-significant increasing trend (up to 3 mm/year) in a large part of Zambia and Central Malawi. However, Malawi and Northern Zambia show a non-significant decreasing trend (up to −5 mm/year). The change in December–April precipitation significantly correlates with El Niño–Southern Oscillation (Indian Ocean Dipole) in Southern (Northern) Zambia and Malawi. To minimize the impact of the observed changes, it is imperative to develop adaptation measures to foster sustainability in the region. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change has already affected drought severity and risk across many regions, and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below‐normal precipitation and terminated by average or above‐normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming‐driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought. Here, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29% in the Mediterranean and 32% and 6% in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts. Plain Language Summary: Regional warming associated with climate change is already making droughts worse in many places. This trend is expected to continue as global temperatures increase in response to continued emissions of greenhouse gases. With increasing temperatures, soils are projected to lose water to the atmosphere as it draws more and more moisture from the land surface, increasing drought risk. At the same time, climate change is also projected to shift precipitation patterns. This means it is important to understand how changes in rainfall will cause and end droughts in the future. Using state‐of‐the‐art climate models, we investigate how future warming will impact the influence of precipitation on soil moisture in the Mediterranean and Western North America. Our results suggest that current levels of monthly precipitation will be insufficient to alleviate drought conditions in a warmer world. Key Points: Warming causes declines in soil moisture in the Mediterranean and Western North AmericaThe probability of a moderate soil moisture drought increases during both low and high precipitation anomalies, even at 1°C of warmingThe ability of large positive precipitation anomalies to terminate soil moisture droughts will be substantially reduced in a warmer world [ABSTRACT FROM AUTHOR]

Based on a long-term experiment in Prague, established in 1954, we analyzed the effect of weather and seven fertilization treatments (mineral and manure treatments) on winter wheat grain yield (GY) and stability. In total, 23 seasons were analyzed, where a wheat crop followed a summer crop of potatoes. A regression analysis showed that, since the experiment started, there has been a significant increase in the annual daily maximum, average, and minimum temperature of 0.5 °C, and an increase in annual rainfall of 0.3 mm. Grain yield was positively associated with April precipitation, mean daily temperature in October, and daily maximum temperature in February. Yields were most stable between years with two fertilizer treatments that supplied a mean of 47 kg N ha−1yr−1, 54 kg P ha−1yr−1, and 108 kg K ha−1yr−1. The rate of N at which grain yield was optimized was determined according to the linear-plateau (LP) and quadratic response models as 44 kg N ha−1yr−1 for the long-strawed varieties and 87 kg N ha−1yr−1for short-strawed varieties.A gradual increase in yields was observed in all treatments, including the unfertilized control, which was attributed to improved varieties rather than to a changing climate. [ABSTRACT FROM AUTHOR]

Groundwater represents 98% of the world's freshwater resources. These resources have been strongly impacted by the increases in temperature and in the variation in precipitation. Despite many advances, the relationship between climate change and the dynamics of aquifer recharge is still poorly understood. This study includes an analysis of 211 papers using the biblioshiny function in the bibliometric R Package. Additionally, specific papers were selected to identify limits, trends, and negative and positive impacts. The results indicated an average growth of 14.38% and a significant increase in research from 2009. In total, 52 countries have undertaken studies in this field, just over 26% of the total number of countries. In the papers examined, the worst projections related to reductions in recharge were identified for arid and desert areas; the highest recharges were identified in the northern regions and in areas at high altitudes, where recharge capacity is maintained or increases due to rapid snow and glacial melting resulting from temperature increases. Despite the advances achieved, more studies should be extended to analyse groundwater assessment at other latitudes to reach a complete and comprehensive understanding. This understanding should be one of the priorities for water among governments and the scientific community in order to safeguard this precious resource. [ABSTRACT FROM AUTHOR]

Understanding runoff dynamics is vital for effective water management in climate-affected areas. This study focuses on the Dayekou basin in China's Qilian Mountains, known for their high climate variability. Using 25 years of data (1994–2018) on river runoff, precipitation, and temperature, statistical methods were applied to explore the annual variations and climate change impacts on these parameters. Results reveal a significant variability in the river runoff (132.27 to 225.03 mm), precipitation (340.19 to 433.29 mm), and average temperature (1.38 to 2.08 °C) over the period. Decadal rising rates average 17 mm for runoff, 17 mm for precipitation, and 0.25 °C for temperature, with the peak precipitation and runoff occurring in 1998–2000, 2008, and 2016. The annual runoff distribution also exhibited a unimodal pattern, peaking at 39.68 mm in July. The cumulative runoff during low periods constituted only 13.84% of the annual total, concentrated in the second half of the year, particularly during the June-October flood season. The correlation analysis underscored a strong relationship between river runoff and precipitation (correlation coefficient > 0.80), while the temperature correlation was weaker (correlation coefficient < 0.80). This 25-year analysis provides valuable insights into runoff variation, elucidating the interconnected effects of temperature and precipitation in the Dayekou basin, with substantial implications for sustainable development amid climate challenges. [ABSTRACT FROM AUTHOR]

This study analyzes daily temperature and precipitation data collected from 44 weather stations throughout New York, New Jersey, and Connecticut to assess and quantify the historical climatic changes within these states. The study conducts a detailed examination of spatial and temporal trends, focusing on specific stations that best represent the climatic diversity of each area. A critical analysis aspect involves comparing temperature trends in urban and suburban areas, mainly focusing on New York City. The findings reveal a significant upward increasing trend in average temperatures across all seasons, with urban areas, especially NYC, exhibiting the most marked increases. This trend is notably sharp in the spring, reflecting climate change's escalating influence. The study also observes an increase in the annual average temperatures and a concurrent decrease in the variability of temperature ranges, suggesting a stabilization of temperature fluctuations over time. Also, we identified a notable increase in heat wave frequency, more so in urban locales than in their suburban counterparts. Analysis of precipitation patterns, particularly in NYC, reveals a decline in snowfall days, consistent with the general warming trend. The results demonstrate significant trends in seasonal average temperatures, a decrease in the variability of temperatures, and a rise in heat wave occurrences, with urban areas typically experiencing warmer conditions. This comprehensive study highlights the need for a more in-depth analysis of spatial precipitation trends. It underscores the importance of continued research in understanding the multifaceted impacts of climate change, particularly in differentiating urban and rural experiences. [ABSTRACT FROM AUTHOR]

The influence of climate feedbacks on regional hydrological changes under warming is poorly understood. Here, a moist energy balance model (MEBM) with a Hadley Cell parameterization is used to isolate the influence of climate feedbacks on changes in zonal‐mean precipitation‐minus‐evaporation (P − E) under greenhouse‐gas forcing. It is shown that cloud feedbacks act to narrow bands of tropical P − E and increase P − E in the deep tropics. The surface‐albedo feedback shifts the location of maximum tropical P − E and increases P − E in the polar regions. The intermodel spread in the P − E changes associated with feedbacks arises mainly from cloud feedbacks, with the lapse‐rate and surface‐albedo feedbacks playing important roles in the polar regions. The P − E change associated with cloud feedback locking in the MEBM is similar to that of a climate model with inactive cloud feedbacks. This work highlights the unique role that climate feedbacks play in causing deviations from the "wet‐gets‐wetter, dry‐gets‐drier" paradigm. Plain Language Summary: Climate feedbacks, which act to amplify or dampen global warming, play an important role in shaping how the climate system responds to changes in greenhouse‐gas concentrations. Here, we use an idealized climate model, which makes a simplified assumption about how energy is transported in the atmosphere, to examine how climate feedbacks influence the patterns of precipitation and evaporation change under global warming. We find that the cloud feedback acts to narrow the band of rainfall on the equator known as the Intertropical Convergence Zone and that the surface‐albedo feedback acts to shift the location of maximum rainfall. We also find that the cloud feedback accounts for most of the uncertainty associated with feedbacks in regional hydrological change under warming. The idealized model with a locked cloud feedback also simulates a change in precipitation and evaporation that is similar to a comprehensive climate model with an inactive cloud feedback. Key Points: A moist energy balance model (MEBM) is used to investigate the influence of climate feedbacks on regional hydrological changes under warmingCloud feedbacks act to narrow and increase tropical P − E and are the dominant source of feedback uncertainty in regional hydrological changesThe MEBM with a locked cloud feedback largely replicates a climate model with an inactive cloud feedback [ABSTRACT FROM AUTHOR]

Agro-climatic indicators (AgcIs) provide a suitable tool to evaluate the implications of climate change on agriculture by simplifying plant–climate interactions. However, developing reliable AgcIs requires high-quality historical climate datasets. Consequently, reanalysis products (RPs) are frequently used as a potential reference dataset for observed climate in agricultural studies. This study aims to compare five RPs (ERA5, ERA5-Land, SCOPE Climate, FYRE Climate, and RFHR) at reproducing observed AgcIs over France. The RPs are evaluated against the SYNOP meteorological data over the 1996–2012 period, focusing on six AgcIs specific to apple, maize, and vine crops. The findings show that RPs perform well in reproducing temperature-based AgcIs, with some slight discrepancies in areas with complex topography. However, all RPs tend to overestimate precipitation amounts and to underestimate dry days, leading to a poor performance in reproducing precipitation-based AgcIs. This study emphasizes the need for a thorough evaluation of the RPs in developing both temperature-based and precipitation-based AgcIs, especially if findings are intended to support operational agricultural decision-making. [ABSTRACT FROM AUTHOR]

Water is a valuable yet scarce resource in agriculture. Optimizing crop production relies on irrigation, but within the framework of sustainable agriculture, efforts should prioritize reducing irrigation water usage. Unfortunately, climate change increases plant water requirements, consequently heightening the need for irrigation. The aim of the research was to estimate the water needs of asparagus during the fern growth period (21 June–31 August) using the Blaney–Criddle method. The study also aimed to determine trends in changing water needs and estimate precipitation deficits. Calculations were carried out for the years 1981–2020 across four provinces in central Poland. The research indicated that water needs varied between 233 mm and 242 mm, depending on the province. Over the forty-year period, all provinces displayed an increasing trend in water needs, with a rise of 3.1 mm to 6.2 mm per decade. Between 21 June and 31 August, rainfall deficits occurred with varying intensity in all provinces during normal, medium dry and very dry years. The values of water needs and rainfall deficit, calculated as a result of the research, are of key importance in the design, construction, and management of drip irrigation systems for asparagus plantations in central Poland. [ABSTRACT FROM AUTHOR]

Microbial-driven processes, including nitrification and denitrification closely related to soil nitrous oxide (N2O) production, are orchestrated by a network of enzymes and genes such as amoA genes from ammonia-oxidizing bacteria (AOB) and archaea (AOA), narG (nitrate reductase), nirS and nirK (nitrite reductase), and nosZ (N2O reductase). However, how climatic factors and agricultural practices could influence these genes and processes and, consequently, soil N2O emissions remain unclear. In this comprehensive review, we quantitatively assessed the effects of these factors on nitrogen processes and soil N2O emissions using mega-analysis (i.e., meta-meta-analysis). The results showed that global warming increased soil nitrification and denitrification rates, leading to an overall increase in soil N2O emissions by 159.7%. Elevated CO2 stimulated both nirK and nirS with a substantial increase in soil N2O emission by 40.6%. Nitrogen fertilization amplified NH4+-N and NO3−-N contents, promoting AOB, nirS, and nirK, and caused a 153.2% increase in soil N2O emission. The application of biochar enhanced AOA, nirS, and nosZ, ultimately reducing soil N2O emission by 15.8%. Exposure to microplastics mostly stimulated the denitrification process and increased soil N2O emissions by 140.4%. These findings provide valuable insights into the mechanistic underpinnings of nitrogen processes and the microbial regulation of soil N2O emissions. [ABSTRACT FROM AUTHOR]

This paper matched the data for all non-financial listed firms in China from 1990 to 2017 with weather data and used temperature and precipitation to represent climate change. Using daily temperature and daily precipitation data, we constructed temperature bins and precipitation bins. This study presents a potential first empirical analysis that applies the risk perception theory to comprehensively examine the impacts of daily temperature and daily precipitation on firms' debt financing costs. Compared to a day with a suitable temperature, a day with temperatures above 30 °C increases firms' debt financing costs by 0.2411%. Compared to a sunny day, a day with torrential rain increases firms' financing costs by 0.2697%. Approximately $122.13 million and $20.49 million in extra costs were incurred across all firms in 2017. We conducted a series of heterogeneity tests. We found that the negative impacts of climate change on debt financing costs are greater for firms that investor considers more vulnerable. Finally, we found two possible mechanisms. First, from the firm's subjective initiative perspective, firms that respond proactively during seasons of high temperatures and heavy rains can reduce the negative impacts. Second, adverse weather caused by climate change may also increase firms' debt financing costs by blocking travel. These results enrich the literature on firms' debt financing costs and contribute to the understanding of climate change's impact on firms. [Display omitted] • An extra high-temperature day increases firms' debt financing cost by 0.2411%. • An extra heavy-rain day increases firms' debt financing costs by 0.2697%. • The negative impacts will be greater for those firms that investor considers more vulnerable. • Firms' response proactively can reduce the negative impacts. • Climate change also may increase firms' debt financing costs by blocking travel. [ABSTRACT FROM AUTHOR]

Coffee is one of the most traded crops worldwide. In the state of Veracruz, Mexico, coffee has been a strategic crop due to its economic, social, environmental, and cultural characteristics that differentiate it from other crops, contributing to the economy of almost 86,000 producers. Several studies have shown that climate is the main cause of the decrease in coffee production and yield. Due to the multi-faceted importance of coffee for the state, the relationship of coffee production and yield with the variables of precipitation (mm) and temperature (°C) from 2003 to 2022 was analyzed through the implementation of a mathematical model that was able to identify that both the total volume of coffee production is decreasing on average at a rate of 7614.9 Mg year−1 as well as the yield, with a significant decrease of 0.106 Mg year−1. It was also found that the optimum temperature value is 18.7 °C, and the optimal precipitation is 1700 mm for the development of coffee. This model also shows that yield is more sensitive to temperature than to precipitation in the study area. Through the application of surveys to 360 producers in 16 coffee-growing municipalities, seven stressors were identified that together hinder the continuity of the coffee industry in the state. These stressors are (1) economic, (2) climatic, (3) land use, (4) technical, (5) social, (6) political, and (7) other. Finally, some strategies are herein proposed to improve coffee production towards greater sustainability, such as agricultural restructuring at the national, regional, and local levels as well as programs and policies to support producers for the continuity of the crop in the region. [ABSTRACT FROM AUTHOR]

Extreme precipitation events are occurring more intensely in Canada. This can contaminate water sources with enteric pathogens, potentially increasing the risk of acute gastrointestinal illness. This study aimed to investigate the relationship between extreme precipitation and emergency department (ED) visits for acute gastrointestinal illness in Toronto from 2012 to 2022. Distributed lag non-linear models were constructed on ED visit counts with a Quasi Poisson distribution. Extreme precipitation was modelled as a 21-day lag variable, with a linear relationship assumed at levels ≧95th percentile. Separate models were also conducted on season-specific data sets. Daily precipitation and gastrointestinal illness ED visits ranged between 0 to 126 mm, and 12 to 180 visits respectively. Overall, a 10-mm increase in precipitation >95th percentile had no significant relationship with the risk of ED visits. However, stratification by seasons revealed significant relationships during spring (lags 1–19, peak at lag 14 RR = 1.04; 95% CI: 1.03, 1.06); the overall cumulative effect across the 21-day lag was also significant (RR = 1.94; 95% CI: 1.47, 2.57). Extreme precipitation has a seasonal effect on gastrointestinal health outcomes in Toronto city, suggesting varying levels of enteric pathogen exposures through drinking water or other environmental pathway during different seasons. [ABSTRACT FROM AUTHOR]

The process of climate warming significantly affects agroclimatic resources and agricultural production. We study the agroclimatic resources and their variability on the territory of the Republic of Bashkortostan (Russia). The Bashkortostan has a high agricultural potential and holds a leading position in the country in the production of grain crops, potatoes, milk, and honey. Currently, no detailed studies have been conducted for this area to assess the effects of global climate change on agro-climatic resources. World experience shows such research becomes strategically important for regions with powerful agricultural production. We used the sums of average daily air temperatures above 0 and 10 °C, the G.T. Selyaninov hydrothermal coefficient, and the Ped aridity (humidification) index as agroclimatic indicators. We used data of long-term meteorological observations of 30 meteorological stations for the period of 1961–2020. We revealed the long-term dynamics of the agroclimatic indicators and the spatial and temporal regularities in their distribution on the territory of Bashkortostan. There is a steady increase in the sums of average daily air temperatures above 0 and 10 °C. Against this background, aridity increases, which is especially manifested in the southern parts of the Republic of Bashkortostan. We assessed the impact of agroclimatic indicators on the main types of agricultural crops in the republic. We revealed that the greatest positive impact on the yield of oilseeds, cereals, and industrial crops is made by precipitation at the beginning (r = 0.50, r = 0.44, and r = 0.52, respectively) and in the middle of the growing season (r = 0.55, r = 0.76, and r = 0.51, respectively). Temperature and precipitation during the growing season have a complex effect on cereals. This is proven by correlations with HCS and the Ped index (r = 0.45 and r = −0.56, respectively). Aridity at the beginning of the growing season affects the yield of oilseeds and potatoes. This is confirmed by correlations with the Ped index (r = −0.49 and r = −0.52, respectively). In general, the aridity of the growing season has a significant impact on the yield of cereals (r = −0.57). Negative relationships have been found between the air temperature growing season and the yield of potatoes (r = −0.50) and cereals (r = −0.53). The results of the study were compared with data from the Copernicus Climate Change Service database. We identified climate trends under RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios. These scenarios should be taken into account when developing plans for the adaptation of agriculture in the Republic of Bashkortostan to changes in the regional climate. Maximum decrease in precipitation is established for the RCP 6.0 scenario. This can have an extremely negative impact on crop yields. This problem is especially relevant for the southern part of the Republic of Bashkortostan. The information presented in the study will allow for a more effective adaptation of the agricultural sector to current and future climate changes. [ABSTRACT FROM AUTHOR]

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