Changes in climate attributes and harvest area structures jointly determined spatial-temporal variations in water footprint of maize in the Beijing-Tianjin-Hebei region.

Irrigation contributes significantly to boosting crop yield and ensuring food security. However, in the Beijing-Tianjin-Hebei (BTH) region, unsustainable irrigation practices have led to serious outcomes on freshwater resources. Balancing irrigation with crop productivity in this region, currently facing complex challenge, requires a comprehensive understanding of its spatial pattern and thus to seeking for potential optimization of current crop structures. In this study, we employed the concept of water footprint (WFP) to assess the spatial-temporal patterns of water footprint for maize in BTH region at the county level for the years 2005, 2010, 2015, and 2020, untangled the relative impacts on WFP from climate attributes and harvest area structures. Our results showed significant regional heterogeneities in both blue water requirement and green water requirement, ranging from 64.6 mm to 290.7 mm. Yearly anomalies of climate attributes and maize harvest jointly influenced water footprints, with the highest value of 1.06 × 1011 m3 occurring in the year 2015. The green water footprints, linked to precipitation, dominated the total water footprint compared to the blue water footprint associated with irrigation. Additionally, we observed an increasing influence of maize harvest area on the temporal changes in water footprints, with these changes becoming more concentrated in the east-central region over time. Our findings underscore the respective contributions of annual climate attribute changes and harvest area variations at the county level, highlighting regions where urgent interventions are required to enhance the sustainability of water usage for agriculture.

Contrasting carbon cycle responses of semiarid abandoned farmland to simulated warmer-drier and warmer-wetter climates.

Rewilding abandoned farmlands provides a nature-based climate solution via carbon (C) offsetting; however, the C-cycle-climate feedback in such restored ecosystems is poorly understood. Therefore, we conducted a 2-year field experiment in Loess Plateau, China, to determine the impacts of warming (∼1.4 °C) and altered precipitation (±25 %, ±50 %, and ambient), alone or in concert on soil C pools and associated C fluxes. Experimental warming significantly enhanced soil respiration without affecting the ecosystem net C uptake and soil C storage; these variables tended to increase along the manipulated precipitation gradient. Their interactions increased ecosystem net C uptake (synergism) but decreased soil respiration and soil C accumulation (antagonism) compared with a single warming or altered precipitation. Additionally, most variables related to the C cycle tended to be more responsive to increased precipitation, but the ecosystem net C uptake responded intensely to warming and decreased precipitation. Overall, ecosystem net C uptake and soil C storage increased by 94.4 % and 8.2 %, respectively, under the warmer-wetter scenario; however, phosphorus deficiency restricted soil C accumulation under these climatic conditions. By contrast, ecosystem net C uptake and soil C storage decreased by 56.6 % and 13.6 %, respectively, when exposed to the warmer-drier climate, intensifying its tendency toward a C source. Therefore, the C sink function of semiarid abandoned farmland was unsustainable. Our findings emphasize the need for management of post-abandonment regeneration to sustain ecosystem C sequestration in the context of climate change, aiding policymakers in the development of C-neutral routes in abandoned regions.

Process-Informed Subsampling Improves Subseasonal Rainfall Forecasts in Central America.

Subseasonal rainfall forecast skill is critical to support preparedness for hydrometeorological extremes. We assess how a process-informed evaluation, which subsamples forecasting model members based on their ability to represent potential predictors of rainfall, can improve monthly rainfall forecasts within Central America in the following month, using Costa Rica and Guatemala as test cases. We generate a constrained ensemble mean by subsampling 130 members from five dynamic forecasting models in the C3S multimodel ensemble based on their representation of both (a) zonal wind direction and (b) Pacific and Atlantic sea surface temperatures (SSTs), at the time of initialization. Our results show in multiple months and locations increased mean squared error skill by 0.4 and improved detection rates of rainfall extremes. This method is transferrable to other regions driven by slowly-changing processes. Process-informed subsampling is successful because it identifies members that fail to represent the entire rainfall distribution when wind/SST error increases.

Evaluation of biocementation of slope soil for erosion control with low-cost materials.

In this study, biocementation of slope soil was performed using low-cost, commercially available materials to create a nutrient solution with native Cytobacillus hornekea. The high cost of laboratory-grade materials and microbes for biocementation is one of the main obstacles to its popularity. However, the cost of biocementation has been reduced significantly without reducing the strength when low-cost materials were used instead of laboratory-grade materials in this study. Direct shear test results and SEM also proved the suitability of the low-cost biocementation. Artificial rainfall with an intensity of 50-60 mm/h resulted in soil erosion of around 10% and 2% without and with biocementation, respectively. The amount of produced calcium carbonate was around 3.9% while using the low-cost materials with native microbes which is quite comparable with the laboratory-grade materials (3.4%).

The consequences of using microlysimeters: Why microlysimeters grossly overestimate dew amounts in arid regions? A critical review.

Although commonly considered the gold standard for measurement of non-rainfall water (NRW), providing reasonable reliable data for vegetated soils, microlysimeters (MLs) tend to grossly overestimate NRW (primarily in form of dew) on barren soil. In arid and semiarid regions, the reported values may be overestimated by hundreds and even 1000 %. This bias is attributed to (i) the effect of the structure and dimension of the ML (ii) the tacit assumption that the weight difference between morning and the previous midday/evening results from dew or (iii) the belief that the MLs will provide reliable values if the difference in weight would be calculated only from the evening or night. For instance, from the time during which the air temperature reaches the dewpoint temperature or from the time during which condensation takes place on an adjacent leaf-wetness sensor. Calculating dew by the weight difference of MLs led to the notions that the fine-textured soil will necessarily promote higher values of dew, and the notion that higher amounts of dew are expected following days with low relative humidity, both of which hamper our understanding regarding dew formation. The reasons for the apparent different performance of MLs in vegetated (wet) and barren (arid) regions are discussed.

Evaluating rainfall erosivity on the Tibetan Plateau by integrating high spatiotemporal resolution gridded precipitation and gauge data.

High-precision rainfall erosivity mapping is crucial for accurately evaluating regional soil erosion on the Tibetan Plateau (TP) under the backdrop of climate warming and humidification. Although high spatiotemporal resolution gridded precipitation data provides the foundation for rainfall erosivity mapping, the increasing spatial heterogeneity of rainfall with decreasing temporal granularity can lead to greater errors when directly computing rainfall erosivity from gridded precipitation data. In this study, a site-scale conversion coefficient was established so that rainfall erosivity calculated using hourly data can be converted to rainfall erosivity calculated using per-minute data. A revised model was established for calculating the rainfall erosivity based on high-resolution hourly precipitation data from the Third Pole gridded precipitation dataset (TPHiPr). The results revealed a notable underestimation in the original calculation results obtained using the TPHiPr, but strong correlation was observed between the two sets of results. There was a significant improvement in the Nash-Sutcliffe coefficient of efficiency (from -0.39 to 0.80) and the Percent Bias (from -63.95 % to 0.37 %) after model revision. The TPHiPr effectively depict the spatial characteristics of rainfall erosivity on the TP. It accurately reflected the rain shadow area on the northern flank of the Himalayas and the dry-hot valley in the Hengduan Mountains. It also showed high rainfall erosivity values in the tropical rainforest area on the southern flank of the eastern Himalayas. The overall trend of rainfall erosivity has increased on the TP during the period 1981 to 2020, with 65.91 % of the regions exhibiting an increasing trend and 22.25 % showing significant increases, indicating an intensified risk of water erosion. These findings suggest that the 40-year-high spatial resolution rainfall erosivity dataset can provide accurate data support for a quantitative understanding of soil erosion on the TP.

Rainfall Observation Leveraging Raindrop Sounds Acquired Using Waterproof Enclosure: Exploring Optimal Length of Sounds for Frequency Analysis.

This paper proposes a novel method to estimate rainfall intensity by analyzing the sound of raindrops. An innovative device for collecting acoustic data was designed, capable of blocking ambient noise in rainy environments. The device was deployed in real rainfall conditions during both the monsoon season and non-monsoon season to record raindrop sounds. The collected raindrop sounds were divided into 1 s, 10 s, and 1 min intervals, and the performance of rainfall intensity estimation for each segment length was compared. First, the rainfall occurrence was determined based on four extracted frequency domain features (average of dB, frequency-weighted average of dB, standard deviation of dB, and highest frequency), followed by a quantitative estimation of the rainfall intensity for the periods in which rainfall occurred. The results indicated that the best estimation performance was achieved when using 10 s segments, corresponding to the following metrics: accuracy: 0.909, false alarm ratio: 0.099, critical success index: 0.753, precision: 0.901, recall: 0.821, and F1 score: 0.859 for rainfall occurrence classification; and root mean square error: 1.675 mm/h, R2: 0.798, and mean absolute error: 0.493 mm/h for quantitative rainfall intensity estimation. The proposed small and lightweight device is convenient to install and manage and is remarkably cost-effective compared with traditional rainfall observation equipment. Additionally, this compact rainfall acoustic collection device can facilitate the collection of detailed rainfall information over vast areas.

A proposed methodology to evaluate the influence of climate change on drinking water treatments and costs.

Drinking water (DW) production treatments can be affected by climate change, in particular intense rainfall events, having an impact on the availability and quality of the water source. The current study proposes a methodology for the evaluation of the costs of the different treatment steps for surface water (SW) and groundwater (GW), through the analysis and quantification of the main cost items. It provides the details to count for strong variations in the key quality parameters of inlet water following severe rainfalls (namely turbidity, iron, manganese, and E. coli). This methodology is then applied to a large drinking water treatment plant (DWTP) in Italy, which treats both SW, around 70 %, and GW, around 30%. It discusses the overall DW production costs (from 7.60 c€/m3 to 10.43 c€/m3) during the period 2019-2021 and analyzes the contributions of the different treatment steps in water and sludge trains. Then it focuses on the effects on the treatments of significant variations in SW turbidity (up to 1863 NTU) due to intense rainfalls, and on the daily costs of DW with respect to the average (baseline) costs evaluated on the annual basis. It emerges that, when SW has low turbidity levels, the energy-based steps have the biggest contribution on the costs (final pumping 22 % for SW and 10 % for GW, withdrawal 15 % and 14 %, respectively), whereas at very high turbidity levels, sludge greatly increases, and its treatment and disposal costs become significant (up to 14 % and 50 %). Efforts are being made to adopt the best strategies for the management of DWTPs in these adverse conditions, with the aim to guarantee potable water and optimize water production costs. A mitigation measure consists of increasing GW withdrawal up to the authorized flow rate, thus reducing SW withdrawal. In this context, the study is completed by discussing the potential upgrading of the DWTP by only treating GW withdrawn from riverbank filtration. The DW production cost would be 7.76 c€/m3, which is lower than that seen for the same year (2021) with the current plant configuration (8.32 c€/m3).

Vulnerability assessment of aerosol and climate variability for rice and maize yield using EO datasets for sustainable agriculture over India.

Human-generated aerosol pollution gradually modifies the atmospheric chemical and physical attributes, resulting in significant changes in weather patterns and detrimental effects on agricultural yields. The current study assesses the loss in agricultural productivity due to weather and anthropogenic aerosol variations for rice and maize crops through the analysis of time series data of India spanning from 1998 to 2019. The average values of meteorological variables like maximum temperature (TMAX), minimum temperature (TMIN), rainfall, and relative humidity, as well as aerosol optical depth (AOD), have also shown an increasing tendency, while the average values of soil moisture and fraction of absorbed photosynthetically active radiation (FAPAR) have followed a decreasing trend over that period. This study's primary finding is that unusual variations in weather variables like maximum and minimum temperature, rainfall, relative humidity, soil moisture, and FAPAR resulted in a reduction in rice and maize yield of approximately (2.55%, 2.92%, 2.778%, 4.84%, 2.90%, and 2.82%) and (5.12%, 6.57%, 6.93%, 6.54%, 4.97%, and 5.84%), respectively. However, the increase in aerosol pollution is also responsible for the reduction of rice and maize yield by 7.9% and 8.8%, respectively. In summary, the study presents definitive proof of the detrimental effect of weather, FAPAR, and AOD variability on the yield of rice and maize in India during the study period. Meanwhile, a time series analysis of rice and maize yields revealed an increasing trend, with rates of 0.888 million tons/year and 0.561 million tons/year, respectively, due to the adoption of increasingly advanced agricultural techniques, the best fertilizer and irrigation, climate-resilient varieties, and other factors. Looking ahead, the ongoing challenge is to devise effective long-term strategies to combat air pollution caused by aerosols and to address its adverse effects on agricultural production and food security.

Quality of nutritional status assessment and its relationship with the effect of rainfall on childhood stunting: a cross-sectional study in rural Burkina Faso.

OBJECTIVES: In Burkina Faso, one in every four children under 5 years is stunted. Climate change will exacerbate childhood stunting. Strengthening the health system, particularly the quality of nutrition care at primary health facilities, can minimise the adverse climate effect on stunting. Thus, we examined the quality of nutritional status assessment (QoNA) during curative childcare services in primary health facilities in rural Burkina Faso and its relationship with rainfall-induced childhood stunting. STUDY DESIGN: We conducted a cross-sectional analysis using anthropometric, rainfall, and clinical observation data. METHODS: Our dependent variable was the height-for-age z-score (HAZ) of children under 2 years. Our focal climatic measure was mean rainfall deviation (MRD), calculated as the mean of the difference between 30-year monthly household-level rainfall means and the corresponding months for each child from conception to data collection. QoNA was based on the weight, height, general paleness and oedema assessment. We used a mixed-effect multilevel model and analysed heterogeneity by sex and socio-economic status. RESULTS: Among 5027 young (3-23 months) children (mean age 12 ± 6 months), 21% were stunted (HAZ ≤ -2). The mean MRD was 11 ± 4 mm, and the mean QoNA was 2.86 ± 0.99. The proportion of children in low, medium, and high QoNA areas was 10%, 54%, and 36%, respectively. HAZ showed a negative correlation with MRD. Higher QoNA lowered the negative effect of MRD on HAZ (ß = 0.017, P = 0.003, confidence interval = [0.006, 0.029]). Males and children from poor households benefited less from the moderating effect of QoNA. CONCLUSION: Improving the quality of nutrition assessments can supplement existing efforts to reduce the adverse effects of climate change on children's nutritional well-being.

Transport processes of dissolved and particulate nitrogen and phosphorus over urban road surface during rainfall runoff.

Nutrient pollutants serve as indicative pollutants in urban stormwater runoff, and usually coexist and transport in particulate and dissolved phase in runoff, which is complex and crucial for effective pollution control. In this study, nitrogen and phosphorus runoff samples were collected during various natural rainfall events to explore its transport process over urban road surface during rainfall runoff. The results showed that nitrogen mainly exists in the dissolved phase (mean proportion: 62.04 %), while phosphorus mainly exists in the particulate phase (mean proportion: 65.58 %). More nitrogen and phosphorus are present and transported in dissolved phase in initial rainfall runoff over urban roads. Nutrient concentration changes during rainfall events were influenced by factors such as rainfall intensity and surface runoff, resulting in multiple peaks. Transport rate peak and concentration peak did not coincide. The proportion of dissolved total nitrogen in the runoff process ranged mainly between 40 % and 80 %, and the proportion of dissolved ammonia was distributed between 60 % and 100 %. The proportion of dissolved phosphorus was more evenly distributed across each proportion interval. Influenced by the differences in phase proportions, first flush processes of nitrogen and phosphorus are not the same. Urban stormwater management measures should prioritize both the initial concentration peaks and the peaks in nutrient transport rates during rainfall. This approach is essential for enhancing the efficiency of stormwater pollutant collection and treatment.

An epidemiological investigation into the reasons for high bovine tuberculosis incidence in cattle herds of the Burren, Ireland, prior to 2020.

Herd-level bovine tuberculosis (bTB) incidence was examined in the Burren, an area in the west of Ireland where herd owners practice distinctive transhumance practices, with upland winter grazing. Prior to the initiation of our study in 2020, bTB incidence had for many years been unusually high in the Burren in comparison with the rest of the country, although the most recent figures have come down to being closer to the national average. Using data from the period prior to 2020, we mapped bTB infection in Burren herds alongside a range of indicators thought to have an association with it - herd size, herd density, herd type, cattle movement, and badger (Meles meles) population and control data, as well as rainfall and altitude. We also looked at how summary statistics for these variables differed when Burren herds with a history of bTB were compared to other Burren herds, as well as bTB positive and negative herds from outside the Burren. We found that for many indicators Burren herds would be expected to be low risk when compared to other herds in Ireland. An exception to this was for rainfall: hot spot areas for bTB in the Burren were found in areas of higher rainfall, on average herds in the Burren experienced more rainfall than those outside it, and bTB herds in the Burren experienced higher rainfall than non-bTB herds. Separately, for Burren herds only, a logistic regression model was developed to explain bTB breakdown occurrence using a matched case-control approach. Cases were herds which had experienced a new bTB breakdown between 2015 and 2019 (n = 260) and these were matched on herd type and herd size with the same number of herds not experiencing a breakdown during this period. This showed that, of a range of exogenous variables, rainfall was the most strongly associated with herd-level bTB incidence. These results suggest that high levels of exposure to inclement weather, and/or better environmental survival of Mycobacterium bovis in the environment, may contribute to high bTB rates in the Burren. However, as rainfall showed a highly aggregated distribution, this relationship may be due to an unmeasured factor correlated with it. Mapping and graphical output suggested that, although herd sizes in the Burren were on average lower than nationally, within the Burren they were higher in areas of higher prevalence, suggesting that mechanisms associated with herd size, such as increased contacts between and within herd, and with wildlife, may also play a role.

Immunoglobulin G (IgG) specific responses to recombinant Qß displayed MSP3 and UB05 in plasma of asymptomatic Plasmodium falciparum-infected children living in two different agro-ecological settings of Cameroon.

Introduction: in areas with intense perennial malaria transmission, limited data is available on the impact of environmental conditions especially rainfall on naturally acquired immunity against promising malaria vaccine candidates. For this reason, we have compared IgG antibody responses specific to Plasmodium spp. derived MSP3 and UB05 vaccine candidates, in plasma of children living in two areas of Cameroon differing in rainfall conditions. Methods: data about children less than 5 years old was collected during the years 2017 and 2018. Next malaria asymptomatic P. falciparum (Pf) infected children were selected following malaria test confirmation. MSP3 and UB05 specific IgG antibody responses were measured in participant´s plasma using enzyme-linked immunosorbent assay (ELISA). Results: interestingly, IgG antibody responses specific to UB05 were significantly higher (p<0.0001) in Pf-negative children when compared to their asymptomatic Pf-infected counterparts living in monomodal rainfall areas. In contrast, a significantly higher (p<0.0001) IgG response to MSP3 was observed instead in asymptomatic Pf-infected children in the same population. In addition, IgG responses specific to UB05 remained significantly higher in bimodal when compared to monomodal rainfall areas irrespective of children´s Pf infection status (p<0.0055 for Pf-positive and p<0.0001 for negative children). On the contrary, IgG antibody responses specific to MSP3 were significantly higher in bimodal relative to monomodal rainfall areas (P<0.0001) just for Pf-negative children. Conclusion: thus IgG antibody responses specific to UBO5 are a better correlate of naturally acquired immunity against malaria in Pf-negative Cameroonian children especially in monomodal rainfall areas.

Enhanced resilience in urban stormwater management through model predictive control and optimal layout schemes under extreme rainfall events.

Optimizing the layout of urban stormwater management systems is an effective method for mitigating the risk of urban flooding under extreme storms. However, traditional approaches that consider only economic costs or annual runoff control rates cannot dynamically respond to the uncertainties of extreme weather, making it difficult to completely avoid large accumulations of water and flooding in a short period. This study proposes an integrated method combining system layout optimization and Model Predictive Control(MPC)to enhance the system's resilience and effectiveness in flood control. An optimization framework was initially built to identify optimal system layouts, balancing annual average life cycle cost (AALCC) and resilience index. The MPC was then applied to the optimal layout selected using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, aiming to alleviate inundation cost-effectively. The adaptability of MPC to varying sets of control horizons and its efficacy in managing the hydrograph and flood dynamics of urban drainage system were examined. Conducted in Yubei, Chongqing, this study revealed patterns in optimal layout fronts among various extreme design rainfalls, showing that peak position rate and return period significantly influence system resilience. The contribution of MPC to the optimal system layout was particularly notable, resulting in improved instantaneous and overall flood mitigation. The application of MPC increased the resilience index by an average of 0.0485 and offered cost savings of 0.0514 million yuan in AALCC. Besides, our findings highlighted the importance of selecting an optimal set of control horizons for MPC, which could reduce maximum flood depth from 0.43m to 0.19m and decrease conduit peak flow by up to 14% at a flood-prone downstream location.

Nonlinear and abnormal relationship between turbidity and suspended solids concentration in mountainous rivers: A case study of the Lai Chi Wo river in Hong Kong, China.

Suspended solids concentration (SSC) in a river is closely relevant to river water turbidity. Investigation of their relationship in this study is accompanied by observed turbidity and SSC values, which were obtained from the testing results of water samples and monitored conditions in streamflow. The water samples were collected from two observation stations with a broad range of sediment concentrations in the Lai Chi Wo catchment in Hong Kong, China. We classified the target rainfall events into single-peak event type and dual-peak event type for a distinguished discussion of the relationship between SSC and turbidity in this study. At a finer classification, each event is separated into defined processes for the analysis, where two main processes refer to the periods that SSC rises from a normal state to a peak state first and the followed periods that SSC recesses to ordinary status gradually. It is advised by the analysis results that the estimation of SSC through turbidity values should be based on the same rainfall types for the upstream station. However, the results show that the classification of rainfall types does not need to take downstream areas into consideration. Furthermore, current research implies that the individual established connections between SSC and turbidity value at different stages (particularly referring to the rising period and recessing period) could be applied to estimate SSC at the same station via continuous turbidity values for both this and other ungauged stations with similar topographical features in the future. Meanwhile, this research approach provides new insight exploring various behaviors of sediments at different stages during an integral rainfall event. A comparison of distinguished performances of sediment during corresponding stages in a rainfall event makes contributions to diverse relationship between SSC and turbidity in the mountainous river.

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.

Investigation of canopy interception characteristics in slope protection grasses: A laboratory experiment.

Canopy interception significantly affects hydrological processes such as infiltration, runoff and evapotranspiration. Research on grass canopy interception remains limited, and the experimental methods employed differ substantially. To thoroughly investigate the canopy interception characteristics of grass and clarify the methodological differences, five commonly utilized slope protection grass species in temperate regions were cultivated in a laboratory setting, and their canopy interception characteristics were experimentally investigated using the water-balance method (WBM), the water-wiping method (WWM) and the water-immersion method (WIM), respectively. The results showed that the WBM is more accurate for measuring canopy interception in grass, whereas both the WWM and the WIM underestimate grass canopy interception capacity. The canopy interception capacity measured by the WBM was 1.61-2.09 times higher than that of the WWM and 1.93-3.47 times higher than that of the WIM. Grey correlation analysis of the eight evaluated factors indicated that leaf area is the most influential factor affecting canopy interception in grass, followed by rainfall amount, dry mass, rainfall intensity, canopy projection area, leaf contact angle, fresh weight, and average height. There is a negative power function relationship between the interception ratio and the rainfall amount. With increasing rainfall intensity, the canopy interception capacity initially increases and then decreases, peaking at rainfall intensities of 15 to 20 mm/h. Leaf contact angle is a key quantifiable parameter that explains the differences in canopy interception among different grass species, and the canopy interception per unit leaf area decreases as the leaf contact angle increases. This study demonstrates that the WBM provides the most accurate measurements of grass canopy interception compared to the WWM and WIM, and highlights the leaf contact angle as a key factor in explaining interspecies differences. These findings could enhance the understanding of grass canopy interception and guide the selection of experimental methods.

Physiological carry-over effects of variable precipitation are mediated by reproductive status in a long-lived ungulate.

In the age of global climate change, extreme climatic events are expected to increase in frequency and severity. Animals will be forced to cope with these novel stressors in their environment. Glucocorticoids (i.e. 'stress' hormones) facilitate an animal's ability to cope with their environment. To date, most studies involving glucocorticoids focus on the immediate physiological effects of an environmental stressor on an individual, few studies have investigated the long-term physiological impacts of such stressors. Here, we tested the hypothesis that previous exposure to an environmental stressor will impart lasting consequences to an individual's glucocorticoid levels. In semi-arid environments, variable rainfall drives forage availability for herbivores. Reduced seasonal precipitation can present an extreme environmental stressor potentially imparting long-term impacts on an individual's glucocorticoid levels. We examined the effects of rainfall and environmental characteristics (i.e. soil and vegetation attributes) during fawn-rearing (i.e. summer) on subsequent glucocorticoid levels of female white-tailed deer (Odocoileus virginianus) in autumn. We captured 124 adult (≥2.5-year-old) female deer via aerial net-gunning during autumn of 2015, 2016 and 2021 across four populations spanning a gradient of environmental characteristics and rainfall in the semi-arid environment of South Texas, USA. We found for every 1 cm decrease in summer rainfall, faecal glucocorticoid levels in autumn increased 6.9%, but only in lactating females. Glucocorticoid levels in non-lactating, female deer were relatively insensitive to environmental conditions. Our study demonstrates the long-lasting effects of environmental stressors on an individual's glucocorticoid levels. A better understanding of the long-term effects stressors impart on an individual's glucocorticoid levels will help to evaluate the totality of the cost of a stressor to an individual's welfare and predict the consequences of future climate scenarios.

Seasonal mosquito (Diptera: Culicidae) dynamics and the influence of environmental variables in a land use gradient from Yucatan, Mexico.

Mosquito-borne diseases constitute a significant global impact on public and animal health. Climatic variables are recognized as major drivers in the mosquitoes' life history, principally rainfall and temperature, which directly influence mosquito abundance. Likewise, urbanization changes environmental conditions, and understanding how environmental variables and urbanization influence mosquito dynamics is crucial for the integrated management of mosquito-borne diseases, especially in the context of climate change. In this study, our aim was to observe the effect of temperature, rainfall, and the percentage of impervious surface on the abundance of mosquito species over a temporal scale of one complete year of fortnightly samplings, spanning from June 2021 to June 2022 in Yucatan, Mexico. We selected nine localities along an urbanization gradient (three natural, three rural, and three urban) from Mérida City to Reserva de la Biosfera Ría Celestún. Using BG-traps, mosquitoes were collected biweekly at each locality. Additionally, we estimated the percentage of impervious surface. Daily data of the maximum, mean and minimum temperatures, diurnal temperature range and rainfall were accumulated weekly. We calculated the accumulated quantities of temperatures and rainfall and lagged from one to four weeks before sampling for each locality. Generalized linear mixed models were then performed to study the influence of environmental variables and percentage of impervious surfaces on each of the 15 most abundant species. A total of 131,525 mosquitoes belonging to 11 genera and 49 species were sampled with BG-Sentinel traps baited with BG-lure and dry ice. The most frequently significative variable is the accumulated precipitation four weeks before the sampling. We observed a positive relationship between Cx. quinquefasciatus and Cx. thriambus with the diurnal temperature range. For Ae. aegypti, we observed a positive relationship with minimum temperature. Conversely, the percentage of impervious surface serves as a proxy of anthropogenic influence and helped us to distinguishing species exhibiting habitat preference for urban and rural environments, versus those preferring natural habitats. Our results characterize the species-specific effects of environmental variables (temperature, rainfall and impervious surface) on mosquito abundance.

Particle size distribution of total suspended sediments in urban stormwater runoff: Effect of land uses, precipitation conditions, and seasonal variations.

Understanding particle size distribution (PSD) of total suspended sediments in urban runoff is essential for pollutant fate and designing effective stormwater treatment measures. However, the PSDs from different land uses under different weather conditions have yet to be sufficiently studied. This research conducted a six-year water sampling program in 15 study sites to analyze the PSD of total suspended sediments in runoff. The results revealed that the median particle size decreased in the order: paved residential, commercial, gravel lane residential, mixed land use, industrial, and roads. Fine particles less than 125 µm are the dominant particles (over 75%) of total suspended sediments in runoff in Calgary, Alberta, Canada. Roads have the largest percentage of particles finer than 32 µm (49%). Gravel lane residential areas have finer particle sizes than paved residential areas. The results of PSD were compared with previous literature to provide more comprehensive information about PSD from different land uses. The impact of rainfall event types can vary depending on land use types. A long antecedent dry period tends to result in the accumulation of fine particles on urban surfaces. High rainfall intensity and long duration can wash off more coarse particles. The PSD in spring exhibits the finest particles, while fall has the largest percentage of coarse particles. Snowmelt particles are finer for the same land use than that during rainfall events because the rainfall-runoff flows are usually larger than the snowmelt flows.