Precipitation Levels Research Articles

Modelling climate impacts on paediatric sepsis incidence and severity in Bangladesh.

Sepsis is a leading cause of paediatric mortality worldwide, disproportionately affecting children in low- and middle-income countries. The impacts of climate change on the burden and outcomes of sepsis in low- and middle-income countries, particularly in paediatric populations, remain poorly understood. We aimed to assess the associations between climate variables (temperature and precipitation) and paediatric sepsis incidence and mortality in Bangladesh, one of the countries most affected by climate change. We conducted retrospective analyses of patient-level data from the International Centre for Diarrhoeal Disease Research, Bangladesh, and environmental data from the National Oceanic and Atmospheric Administration. Using random forests, we assessed associations between sepsis incidence and sepsis mortality with temperature and precipitation between 2009-22. A nonlinear relationship between temperature and sepsis incidence and mortality was identified. The lowest incidence occurred at an optimum temperature of 26.6°C with a gradual increase below and a sharp rise above this temperature. Higher precipitation levels showed a general trend of increased sepsis incidence. A similar distribution for sepsis mortality was identified with an optimum temperature of 28°C. Findings suggest that environmental temperature and precipitation play a role in paediatric sepsis incidence and sepsis mortality in Bangladesh. As children are particularly vulnerable to climate impacts, it is important to consider climate change in health care planning and resource allocation, especially in resource-limited settings, to allow for surge capacity planning during warmer and wetter seasons. Further prospective research from more globally representative data sets will provide more robust evidence on the nature of the relationships between climate variables and paediatric sepsis worldwide.

Assessing global drought conditions under climate change: A comparison of stationary and non-stationary approaches and identification of hotspot regions

Droughts pose significant threats to both human society and the surrounding environment. Because of the anticipated intensification of drought conditions owing to climate change, assessing their impacts using dynamic and non-stationary methodologies is considerably required. This study employed temperature and precipitation data derived from a comprehensive set of 15 global climate models (GCMs) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) within the framework of the Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset to address crucial inquiries related to drought. Specifically, we explored the transformations that drought conditions may undergo with increasing temperature and precipitation levels. The study identified geographical areas likely to become hotspots of global warming and compared drought indices that incorporate non-stationarity with those that do not in assessing the evolution of global drought conditions. The findings revealed that indices using stationary approaches with fixed distribution parameters underestimate or overestimate future drought conditions because they overlook trends such as decreasing precipitation and increasing temperatures in drought variables. This results in an average misestimation of approximately 10 %–20 % in duration and severity in the far future in the sub-regions. Specifically, underestimations were detected in the high latitudes of the Northern Hemisphere (Alaska and Northern Asia), northwestern China, India, and northern and eastern Africa. Conversely, the stationary drought index exhibited maximum overestimations in the Amazon, Western Australia, the Mediterranean region, and South Africa regions for future drought projections. Combining the results of the multi-drought characterization, including frequency, duration, severity, and spatial extent, we identified Northern North America, the Amazon region, the Mediterranean region, south-central Africa, and southeastern Asia as hotspot regions for drought responses to global warming. In future drought warnings, particular attention should be directed toward regions where drought is underestimated.

Crack Length of Elastomeric Sealants and Their Service Life in Contrasting Canadian Climates: Effects of Climate Change.

The longevity of polymer-based sealant and jointing products, including elastomers, significantly depends on the level of exposure to sunlight and joint movement. These factors are particularly crucial in the application of polymers in construction due to their susceptibility to degradation under environmental conditions. For instance, diurnal cycles of contraction and dilation, arising from daily temperature fluctuations, impose significant stress on sealants and joints, impacting their durability over time. The elastic nature of polymeric sealants enables them to endure these cyclic mechanical loads. Athough there is considerable information on sealant durability obtained from laboratory accelerated aging, there is limited knowledge about the effect of climatic factors using historical and projected weather data on the durability and expected service life of these products. This study employed the Shephard crack growth model to predict the performance of sealants in a Canadian context; the crack growth and time-to-failure of hypothetical silicone sealants were investigated across 564 locations, for which historical climate data were obtained from 1998 to 2017, including gridded reanalysis data for the period of 1836-2015. The historical climate data were classified into four climate categories, and crack growth was estimated based on historical climatic data within the valid range for the Shephard model, revealing that locations in colder climates with lower levels of precipitation typically exhibit higher cumulative crack growth. The impact of climatic variation and environmental stressors on the longevity of sealants in the context of climate change was also investigated using future projected data.

Evaluating climate-dependent distribution of orthohantaviruses with monitoring wild rodents: One Health Perspective†.

Orthohantaviruses, cause hemorrhagic fever with renal syndrome, nephropathia epidemica, and hantavirus pulmonary syndrome, are major public health problems all over the world. Wild rodent surveillance for orthohantaviruses is of great importance for the preparedness against these human infections and the prediction of possible outbreak regions. Thus, we aimed to screen orthohantaviruses in wild rodents in Southern Anatolia, where the area has some of the glacial period refugia in the Mediterranean Basin, and interpret their current epidemiology with climatic biovariables in comparison with previously positive regions.We trapped muroid rodents between 2015 and 2017, and screened for orthohantaviruses. Then, we evaluated the relationship between orthohantavirus infections and bioclimatic variables. In spite of the long-term and seasonal sampling, we found no evidence for Orthohantavirus infections. The probable absence of orthohantaviruses in the sampling area was further evaluated from the climatic perspective, and results led us suggest that Orthohantavirus epidemiology might be relatively dependent on precipitation levels in driest and warmest quarters, and temperature fluctuations.These initial data might provide necessary perspective on wild rodent surveillance for orthohantaviruses in other regions, and help to collect lacking data for a such habitat suitability study in a bigger scale in the future.

Limnological Characteristics and Relationships with Primary Productivity in Two High Andean Hydroelectric Reservoirs in Ecuador

Studies on limnology are essential to reservoir management; nevertheless, few are known about the limnological features of the Andean reservoirs in Ecuador. To overcome this limitation in the information, from December 2018 to December 2019, the limnological characteristics of El Labrado and Chanlud reservoirs in the Machángara river basin (Ecuador south) were examined. Using the light/dark bottles technique, the primary productivity (PP) of phytoplankton was studied in conjunction with (1) vertical profiles of oxygen concentrations, water temperature, nitrogen, phosphorus, alkalinity, and heterotrophic bacteria; (2) Secchi disk transparency; and (3) meteorological factors such as wind force, precipitation, and water level. Data indicate that both reservoirs are polymictic, with alkaline waters, low nutrients, and low PP rates. Despite this, a principal component analysis revealed that Chanlud exhibits higher nitrogen, alkalinity, heterotrophic bacteria, and PP values. In two approaches through multiple linear regression analysis, each per reservoir, the PP was explained mainly by water temperature, depth, light, heterotrophic bacteria, and meteorological parameters. The low concentrations of nutrients and the low residency time explain the low PP values. Likewise, the altitudinal factor (i.e., both reservoirs are 3400 m above sea level) and the low human perturbations in surrounding reservoir zones play a crucial role in explaining their poor PP. Notwithstanding the low metabolic rates, clear seasonal trends were observed in both reservoirs; the lowest PP rates occurred during the cold season. To our knowledge, this is the first limnological study of high Andean reservoirs in Ecuador. These findings should be part of Andean reservoir management protocols, contributing significantly to local conservation efforts. Additionally, they could be extrapolated as a frame of reference to similar eco-hydrological systems.

Extreme weather has variable effects on reproductive success of grassland songbirds at the northern extent of their range

Abstract Grassland songbirds breeding in Canada and the United States have experienced significant population declines likely because of habitat loss and degradation. Many climate change models predict an increase in the frequency, intensity, and duration of extreme precipitation and temperature events that could place further pressures on declining species. We monitored the fate of 1,868 individual nesting attempts of 7 grassland songbird species in response to various precipitation and temperature measures over a 10-yr period (1997 to 2002 and 2004 to 2008) in Saskatchewan, Canada. Daily nest survival rates of 5 species, including 3 at-risk species, were negatively influenced by high levels of precipitation, although the amount of precipitation where declines in daily nest survival occurred varied. Daily nest survival rates of 2 species were negatively correlated with high temperatures. We failed to detect any relationship between precipitation or temperature and the number of fledglings produced from successful nests. Extreme weather events could add additional stressors to declining populations of grassland birds in Canada. Increases in the frequency and intensity of extreme weather, specifically extreme precipitation events and short-term high temperatures, will likely lead to lower reproductive success for several species compared to current levels. This may be especially problematic for management of Anthus spragueii (Sprague’s Pipit) and Centronyx bairdii (Baird’s Sparrow), where a large proportion (> 75%) of the breeding population occurs near the northern edge of the Great Plains. The continuing loss and degradation of northern grasslands may limit the ability of these species to disperse and find favorable climate conditions.

Evaluation and Comparison of Five Long-Term Precipitation Datasets in the Hang-Jia-Hu Plain of Eastern China

This study analyzed the applicability of five long-term precipitation datasets in the Hang-Jia-Hu Plain of eastern China based on meteorological observation data. The accuracy of each dataset at different time scales (yearly, monthly) was analyzed. Besides, their spatiotemporal distributions and differences in precipitation event frequency were also compared. The results indicate that the high-resolution (1 day, 1 km) and long-term (1961–2019) gridded dataset for temperature and precipitation across China (HRLT) exhibited the best overall performance at the annual scale, while the long-term, gauge-based gridded precipitation dataset for the Chinese mainland (CHM_PRE) performed the best at the monthly scale. The dataset of monthly precipitation with a resolution of 1 km in China from 1960 to 2020 (HHU) and the China Meteorological Forcing Dataset (CMFD) tend to overestimate the local precipitation amounts, while the other three products are characterized by an underestimation. The mean result of the five datasets indicates a slight, statistically insignificant rise in precipitation, by 4.19 mm annually, with an overall multi-year average of 1303.28 mm. The analysis of the five datasets successfully captures the spatial precipitation patterns across the Hang-Jia-Hu Plain, characterized by higher precipitation levels in the southwest and lower in the northeast. Although the interannual variability displays general consistency, there are significant discrepancies in the interannual growth rates and the spatial distribution of significance across different regions. This study can provide a reference for the accuracy of precipitation data in the fields of hydrology, meteorology, agriculture, and ecology, facilitating the analysis of uncertainties in related research.

Soil type and precipitation level have a greater influence on fungal than bacterial diversity in serpentine and non‐serpentine biological soil crusts

AbstractSerpentine soils are characterized by nutrient imbalances and high levels of potentially toxic metals (PTMs). These soils host depauperate plant communities of species with specialized adaptations. Initial studies showed that South African serpentine soils harbor distinct biocrust algal and cyanobacterial species compared to adjacent non‐serpentine soils, with these communities further differing based on high and low precipitation levels. Here, we investigated the bacterial and fungal diversity of biological soil crusts from serpentine and non‐serpentine soils at two precipitation levels. The bacterial and fungal communities were characterized using 16S rDNA and ITS metabarcoding, respectively. No significant differences could be found in bacterial richness and community structure. Nevertheless, bacterial taxa such as Archangium, Candidatus Solibacter, Chthoniobacter, and Microvirga were more abundant in serpentine biocrusts or biocrusts receiving lower precipitation. The fungal community structure was distinct between serpentine and non‐serpentine soils (p = 0.027) and between high and low precipitation (p = 0.018). Furthermore, fungal diversity was lowest in the drier, serpentine biocrusts compared to non‐serpentine (p = 0.001) and serpentine crusts receiving higher precipitation (p = 0.002). The fungal genera, Ramimonilia and Vishniacozyma, which are known to be resistant or tolerant to PTMs and other environmental extremes, were significantly more abundant (p = 0.036 and p = 0.016, respectively) in serpentine biocrusts, with the latter indicating serpentine habitats. This study concluded that soil type influenced the fungal alpha diversity, specifically in the serpentine soil, resulting in a decrease in fungal species richness. Furthermore, precipitation influenced fungal beta diversity by shaping distinct fungal communities found in the biocrusts of serpentine and non‐serpentine soils.

Assessing the Climate Change Impacts on Maize Production in the Slovak Republic and Their Relevance to Sustainability: A Case Study

Climate change poses a significant challenge to the agricultural sector, with far-reaching implications on a global scale. As the agriculture sector plays a critical role in the economy of the Slovak Republic, it is crucial to understand the impacts of climate change and, with it, the vulnerabilities that agricultural practices face. Agricultural production and food sustainability are intricately linked to various factors, including population growth and the effects of climate change. This paper focuses on analyzing the production of maize in Slovakia and identifying the factors driving its cultivation. We aim to assess how climate factors influence maize yields across different temperature and precipitation levels through comprehensive data analysis and statistical methods. By utilizing the stochastic production function proposed by Just and Pope (1979) for 1996 to 2022 and estimating model parameters using GRETL software, we aim to provide insights into the relationship between climate change and maize production. Furthermore, we explore the implications of our findings for the sustainability of agricultural practices in Slovakia. Our analysis reveals that the impact of temperature and precipitation on maize yield varies by month and exhibits a nonlinear nature, with climate changes generally exerting a negative influence. Understanding these dynamics is crucial for developing sustainable agricultural strategies that can mitigate the adverse effects of climate change on maize production and ensure long-term food security.

Modeling the water use associated with energy consumption changes on saltwater intrusion in the Pearl River estuary, China

The intrusion of saline tide into estuaries is one of the major environmental issues impedding the regional development of the Pearl River Estuary, which has been exacerbated by increasing water use associated with energy consumption in the estuary areas. However, the relationship among water use, energy consumption and saltwater intrusion remains ambiguous. Firstly, this paper established a k-nearest neighbor model that identified the correlation between inputs of precipitation and sectoral energy consumption and output of runoff in the Humen Channel as part of the Pearl River Estuary during 2019–2020. Then, the Finite–Volume Community Ocean Model (FVCOM) was employed to explore the process-based mechanism between runoff and salinity via three scenarios simulated for the periods 2030–2031 and 2060–2061 with different water use and precipitation levels. Finally, the impacts of sectoral energy consumption on saltwater intrusion under the different scenarios were analyzed. The results showed that the increase of the energy consumption was positively correlated to runoff, especially in the wet season of Humen Channel. The monthly average salinity exhibited remarkable seasonal variations with similar trends under three scenarios. Totally 654 days with salinity exceeding the standard were projected to take place in the downstream of Humen Channel during the simulation period.

Cover collapse sinkhole formation is delayed in time and uncorrelated to distance from quarry in a long-term study of a karst basin

Collapse sinkholes are problematic for the hazards they bring to property, infrastructure, and human life but the prediction of their formation in time and space remains elusive. We make use of long-term data gathered in a small, highly monitored, hydrologically constrained basin; Primrose Creek, Bucks County, Pennsylvania, USA, to examine the relation between groundwater extraction, precipitation, terrain position, and cover collapse sinkhole development. The selected site is unique as a natural laboratory to explore induced sinkhole processes in that it is a clearly demarcated topographic basin with geological structural and lithologic boundaries; the stressor is extreme, has been plainly identified, and effectively captures all upstream runoff and groundwater; the groundwater withdrawals and water-level elevations have been closely monitored over a period of 20 years; and the general record of land conditions goes back more than a century. We evaluated the history of a carbonate-rock quarry, its development and expansion over many decades, as well as associated precipitation and ground-water level data, and cover collapse sinkhole occurrence within the basin. Interception of discrete high conductivity zones in the Paleozoic carbonate rocks by quarry expansion was an important factor in propagating collapse occurrence. Collapses occurred mainly, though not exclusively, along drainageways and at lithologic boundaries. They formed in time-based clusters with delay of up to several years. Surprisingly, distance of collapse formation from the pumping area was not directly correlated with time elapsed; i.e., collapses did not begin to form close to the quarry, and then later form farther away. Monitoring wells were unsuccessful in delineating the pumping zone of influence although some documented water table decline and response to weather and anthropogenic events. This comprehensive study shows that in order to successfully monitor and control impacts from quarry dewatering in Paleozoic carbonate rocks it is critical to 1) develop a detailed conceptual model of groundwater pathways, 2) try to avoid excavating into high permeability zones, 3) clearly document karst features when exposed, and 4) carefully site a suitable number of monitoring wells and collect data at short intervals.

Climate change to exacerbate the burden of water collection on women’s welfare globally

Climate change is aggravating water scarcity worldwide. In rural households lacking access to running water, women often bear the responsibility for its collection, with adverse effects on their well being through long daily time commitments, physical strain and mental distress. Here we show that rising temperatures will exacerbate this water collection burden globally. Using fixed-effects regression, we analyse the effect of climate conditions on self-reported water collection times for 347 subnational regions across four continents from 1990 to 2019. Historically, a 1 °C temperature rise increased daily water collection times by 4 minutes. Reduced precipitation historically increased water collection time, most strongly where precipitation levels were low or fewer women employed. Accordingly, due to warming by 2050, daily water collection times for women without household access could increase by 30% globally and up to 100% regionally, under a high-emissions scenario. This underscores a gendered dimension of climate impacts, which undermines womens’ welfare.

Drivers of barrier island water-table fluctuations and groundwater salinization

Barrier islands are threatened by climate change as sea-level rise and higher frequency storm surge lead to more flooding and saltwater intrusion. Vegetation plays a vital role in preventing erosion of barrier islands due to aeolian and hydrological forces. However, vegetation on barrier islands is threatened by rising water tables causing hypoxic conditions and storm-surge overwash introducing saline water to the root zone. To better protect barrier island ecosystems, it is critical to identify the relative influence of different hydrological drivers on water table elevation and salinity, and understand how this influence varies spatially and temporally. In this study, three barrier island sites were instrumented with groundwater wells monitoring water level and specific conductance. Using these data, a set of transfer function noise models were calibrated and used to determine the relative influence of hydrologic drivers including precipitation, evapotranspiration, bay and ocean water levels, and wave height on groundwater levels and specific conductance. We found that drivers of water-level change and specific conductance vary strongly among sites, depending primarily on the surface water connectivity and the geology of the island. Sites with close connection to inlets showed more salinization and responded to a larger number of drivers, while sites that were poorly connected to the ocean responded to fewer drivers.

GIS-based spatio-temporal analysis of rainfall trends under climate change in different agro-ecological zones of Wolaita zone, south Ethiopia

Understanding the spatiotemporal dynamics of climatic conditions within a region is paramount for informed rural planning and decision-making processes, particularly in light of the prevailing challenges posed by climate change and variability. This study undertook an assessment of the spatial and temporal patterns of rainfall trends across various agro-ecological zones (AEZs) within Wolaita, utilizing data collected from ten strategically positioned rain gauge stations. The detection of trends and their magnitudes was facilitated through the application of the Mann–Kendall (MKs) test in conjunction with Sen's slope estimator. Spatial variability and temporal trends of rainfall were further analyzed utilizing ArcGIS10.8 environment and XLSTAT with R programming tools. The outcomes derived from ordinary kriging analyses unveiled notable disparities in the coefficient of variability (CV) for mean annual rainfall across distinct AEZs. Specifically, observations indicated that lowland regions exhibit relatively warmer climates and lower precipitation levels compared to their highland counterparts. Within the lowland AEZs, the majority of stations showcased statistically non-significant positive trends (p > 0.05) in annual rainfall, whereas approximately two-thirds of midland AEZ stations depicted statistically non-significant negative trends. Conversely, over half of the stations situated within highland AEZs displayed statistically non-significant positive trends in annual rainfall. During the rainy season, highland AEZs experienced higher precipitation levels, while the south-central midland areas received a moderate amount of rainfall. In contrast, the northeast and southeast lowland AEZs consistently received diminished rainfall across all seasons compared to other regions. This study underscores the necessity for the climate resilient development and implementation of spatiotemporally informed interventions through implementing region-specific adaptation strategies, such as water conservation measures and crop diversification, to mitigate the potential impact of changing rainfall patterns on agricultural productivity in Wolaita.

Spatio-Temporal distribution of a vector of cutaneous leishmaniasis: Pintomyia longiflocosa, in a population from the Colombian Andean Mountains.

Leishmaniasis, a neglected disease and public health concern, is associated with various factors such as biological, social, economical conditions and climate, increasing the risk of human infection. Understanding the population dynamics of the vectors, like Pintomyia longiflocosa, and its relationship with ecological variables is crucial for developing effective strategies to control sand fly populations and combat cutaneous leishmaniasis in a tropical country like Colombia. Adult sand flies were collected in three different sample locations: outdoor, indoor, and peri-domestic areas in three houses located in the rural settlement of Campoalegre (Huila) between February 2020 and February 2021, using the CDC light traps. The sand fly density was quantified and associated with the sample locations and the sampling months using Analysis of Variance and Pearson correlations. In the period of the sample, 98.86% of sand fly collected was identified as Pi. longiflocosa. The density of this species was significantly different between males and females, the latter contributing more to density in all sample locations (P<0.0001). The outdoor was the sample location with the highest and most significative density in this study (70%, P = 0.04). The density of these sand flies is related to the seasonality of Campoalegre, revealing a density peak from February and June to October (P < 0.05). Finally, precipitation is the environmental variable prominently linked to the density pattern, showing a negative correlation with it. Months with the highest precipitations show the lowest values of Pi. longiflocosa abundance. Our investigation reveals a inverse correlation between precipitation levels and the abundance of Pi. longiflocosa in Campoalegre (Huila), particularly in outdoor areas. This suggests that vector control strategies to periods of reduced precipitation in outdoor settings could offer an effective approach to minimizing cases of cutaneous leishmaniasis in the region.

Comparative Analysis of Maize Physico-Chemical Parameters and Mycotoxin Levels in Dual Environments.

Maize (Zea mays L.) stands as a vital staple food globally, holding significant nutritional and economic value. However, its susceptibility to mycotoxin contamination under stressful environmental conditions poses a considerable concern. This study aimed to assess the quality and pasting characteristics of maize varieties across two distinct regions and examine the occurrence of mycotoxins influenced by climatic factors. Five maize varieties were cultivated in triplicate in the Golegã and Coruche regions. The nutritional composition (protein, fat, fiber, ash, starch, and lutein), pasting properties, and mycotoxin levels were evaluated. A statistical analysis revealed notable differences in the nutritional profiles of the maize varieties between the two regions, particularly in the protein and lutein content. The peak viscosity ranged from 6430 to 8599 cP and from 4548 to 8178 cP in the maize varieties from the Coruche and Golegã regions, respectively. Additionally, a significant correlation was observed between the climatic conditions and the grain nutritional quality components (p < 0.05). The M variety showed the highest ash content, protein content, final viscosity, and setback viscosity and the lowest peak viscosity. The Y variety revealed the lowest fat, fiber, and lutein content and the maximum peak viscosity. The incidence of mycotoxins was notably higher in the varieties from Coruche, which was potentially attributable to higher temperatures and lower precipitation levels leading to more frequent drought conditions. Fumonisin B1 was detected in 58% of the varieties from Coruche and 33% of the samples from Golegã, while deoxynivalenol was found in 87% and 80% of the varieties from Coruche and Golegã, respectively. The H variety, which was harvested in Coruche, exhibited the highest number of fumonisins and higher amounts of protein, lutein, and fat, while fumonisins were not detected in the Golegã region, which was potentially influenced by the precipitation levels. The K variety revealed higher protein and lutein contents, a lower amount of fat, excellent pasting properties (a higher peak viscosity and holding strength and a lower peak time), and no fumonisins B1 or B2. This variety may be considered well adapted to higher temperatures and drier conditions, as verified in the Coruche region. In conclusion, our study underscored the profound impact of environmental factors on the quality and occurrence of mycotoxins in maize varieties.

Precipitation-induced landslide risk escalation in China’s urbanization with high-resolution soil moisture and multi-source precipitation product

Landslides pose a formidable natural hazard. Accurate risk assessment of landslides triggered by precipitation heavily relies on hydrometeorological factors, specifically precipitation and soil moisture. However, the insufficient ground-based observations and the coarse spatio-temporal resolution hinder the performance of landslide prediction. It is not clear what hydrometeorological thresholds and triggering mechanisms are more likely to trigger landslides in China, particularly in the context of rapid urbanization. To address these questions, this study investigated 1504 shallow landslide events in Chinese urban and non-urban areas from 2007 to 2019. It utilized daily 1 km soil moisture at various depths (20–100 cm) and multi-source precipitation datasets, including gauge-based gridded dataset, in conjunction with three multi-source fusion precipitation products (Multi-Source Weighted-Ensemble Precipitation − MSWEP, the Climate Hazards Group InfraRed Precipitation with Station dataset − CHIRPS, and the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement − GPM-IMERG), along with dynamic urban impervious area datasets. It aims to determine the optimal multi-source precipitation predictor, the critical soil moisture depth that triggers landslides, and to establish the hydrometeorological thresholds for landslides. Additionally, the impact of urbanization on landslide occurrences was estimated by comparing antecedent precipitation accumulation, soil moisture, and impervious surface ratio dynamics between urban and non-urban areas. The results indicated that a combination of 2-day cumulative CHIRPS precipitation and 100 cm soil moisture provided the most accurate predictions for landslides in urban regions of China (accuracy = 88.5 %), outperforming interpolated ground-based observations and other fusion products. Specifically, landslides become more prone when antecedent cumulative rainfall surpasses 97.42 mm in 2 days and soil moisture exceeds 39.6 % m3/m3 saturation in China. Urban areas experienced high antecedent precipitation levels, lower precipitation (64.40 mm) threshold and soil moisture threshold (38.9 %), and shorter durations at landslide sites compared to non-urban areas (71.90 mm, 41.4 %, and 7 days, respectively). The process of urbanization is observed to decrease soil moisture levels while concurrently elevating rainfall amounts. This phenomenon, combined with anthropogenic activities, including distance from roads and urban impervious surface expansion, contributes to 44.6 % of the causes of landslides by reducing slope stability and increasing the presence of loose material. These findings have implications for landslide warnings in urban areas with limited measurements and contribute to understanding urbanization’s impact on landslide risks in developing nations.

Characteristics of precipitation changes during tropical cyclone processes in China from 1980 to 2019

Tropical cyclones (TCs) and their associated intense rainfall are among the most significant natural disasters. Exploring the characteristics of tropical cyclone precipitation (TCP) has always been a challenging issue in TC research. This study utilized the TC track data from the International Best Track Archive for Climate Stewardship and precipitation data from the multi-source weighted-ensemble precipitation covering the years 1980–2019, to examine shifts in precipitation rates and peak precipitation levels before and after TC landfall. The results highlight several key findings: (1) Precipitation during the TC landfall process is relatively stable beforehand but tends to decrease slightly after landfall. Generally, the maximum precipitation occurs during the landfall. (2) From 1980 to 2019, the rate of precipitation changes before landfall has significantly increased. Conversely, after the year 2000, the rate of precipitation changes after landfall has significantly decreased. (3) Over the past 40 years, while peak precipitation levels of landfalling TCs have remained relatively constant, the total precipitation has shown an increasing trend, particularly in regions like the main island of Hainan, southern Zhejiang, and Shanghai, which are characterized by high peak precipitation. The results help clarify the TC processes and provide reference points for parameter selection in regional TCP modeling.

Key drivers of vulnerability to rainfall flooding in New Orleans

IntroductionFuture urban stormwater flood risk is determined by the confluence of both climate-driven changes in precipitation patterns and the effectiveness of flood mitigation systems, such as urban drainage and pump systems. This is especially true in coastal cities protected by levee systems like New Orleans, where even present-day rainfall would be enough to cause serious flooding in the absence of extensive stormwater drainage and pumping. However, while the uncertainties associated with climate change have been well studied, uncertainties in infrastructure performance and operation have received less attention.MethodsWe investigated how these interrelated sets of uncertainties drive flood risk in New Orleans using a Robust Decision Making (RDM) approach. RDM is a framework for Decision Making Under Deep Uncertainty (DMDU) that leverages simulation models to facilitate exploration across many possible futures and the identification of decision-relevant scenarios. For our work, we leveraged a detailed Storm Water Management Model (SWMM) representation of the New Orleans urban stormwater management system to examine flood depths across the city when faced with different levels of future precipitation, sea-level rise, drainage pipe obstruction, and pumping system failure. We also estimated direct flood damage for each neighborhood in the city for this scenario ensemble. These damage estimates were then subjected to vulnerability analysis using scenario discovery—a technique designed to determine which combinations of uncertainties are most stressful to the system in terms of an outcome of interest (excess flood damage).ResultsOur results suggest that key drivers of vulnerability depend on geographic scale. Specifically, we find that possible climate-driven precipitation increases are the most important determinant of vulnerability at the citywide level. However, for some individual neighborhoods, infrastructure operation challenges under present day conditions are a more significant driver of vulnerability than possible climate-driven precipitation increases.

Effects of Climatic Disturbance on the Trade-Off between the Vegetation Pattern and Water Balance Based on a Novel Model and Accurately Remotely Sensed Data in a Semiarid Basin

Vegetation is a natural link between the atmosphere, soil, and water, and it significantly influences hydrological processes in the context of climate change. Under global warming, vegetation greening significantly aggravates the water conflicts between vegetation water use and water resources in water bodies in arid and semiarid regions. This study established an improved eco-hydrological coupled model with related accurately remotely sensed hydrological data (precipitation and soil moisture levels taken every 3 j with multiply verification) on a large spatio-temporal scale to determine the optimal vegetation coverage (M*), which explored the trade-off relationship between the water supply, based on hydrological balance processes, and the water demand, based on vegetation transpiration under the impact of climate change, in a semiarid basin. Results showed that the average annual actual vegetation coverage (M) in the Hailar River Basin from 1982 to 2012 was 0.62, and that the average optimal vegetation coverage (M*) was 0.56. In 67.23% of the region, M* was lower than M, which aggravated the water stress problem in the Hailar River Basin. By identifying the sensitivity of M* to vegetation characteristics and meteorological parameters, relevant suggestions for vegetation-type planting were proposed. Additionally, we also analyzed the dynamic threshold of vegetation under different climatic conditions, and we found that M was lower than M* under only four of the twenty-eight climatic conditions considered (rainfall increase by 10%, 20%, and 30% with no change in temperature, and rainfall increase by 20% with a temperature increase of 1 °C), thereby meeting the system equilibrium state under the condition of sustainable development. This study revealed the dynamic relationship between vegetation and hydrological processes under the effects of climate change and provided reliable recommendations to support vegetation management and ecological restoration in river basins. The remote sensing data help us to extend the model in a semiarid basin due to its accuracy.