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.

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.

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.

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.

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.

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).

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.

Leaching characteristics and environmental impact of heavy metals in tailings under rainfall conditions: A case study of an ion-adsorption rare earth mining area.

Following ion-adsorption rare earth mining, the residual tailings experience considerable heavy metal contamination and gradually evolve into a pollution source. Therefore, the leaching characteristics and environmental impact of heavy metals in ion-adsorption rare earth tailings require immediate and thorough investigation. This study adopted batch and column experiments to investigate the leaching behaviour of heavy metals in tailings and assess the impact of tailings on paddy soil, thereby providing a scientific basis for environmental protection in mining areas. The results showed that Mn, Zn, and Pb contents were 431.67, 155.05, and 264.33 mg·kg-1, respectively, which were several times higher than their respective background values, thereby indicating significant heavy metal contamination in the tailings. The batch leaching experiment indicated that Mn and Pb were priority control heavy metals. Heavy metals were divided into fast and slow leaching stages. The Mn and Pb leaching concentrations far exceeded environmental limits. The DoseResp model perfectly fitted the leaching of all heavy metals from the tailings (R2 > 0.99). In conjunction with the findings of the column experiment and correlation analysis, the chemical form, rainfall pH, ammonia nitrogen, and mineral properties were identified as the primary factors controlling heavy metal release from tailings. Rainfall primarily caused heavy metal migration in the acid-extraction form from the tailings. The tailing leachate not only introduced heavy metals into the paddy soil but also caused the transformation of the chemical form of heavy metals in the paddy soil, further exacerbating the environmental risk posed by heavy metals. The study findings are significant for environmental conservation in mining areas and implementing environmentally friendly practices in rare earth mining.

Reproductive biology of Lepidocephalichthys guntea: a key conservation approach considering environmental factors in Payra River, Bangladesh.

The guntea loach, Lepidocephalichthys guntea, is categorically common freshwater fish in Southeast Asia. Current study is the first elucidation on the reproductive feature of L. guntea including population structure, sex ratio (SR), size at first maturity (Lm), breeding period, and condition factor, emphasizing on the effect of environmental factors on reproduction of this fish in the Payra River (Southern Bangladesh) during July 2021 to June 2022. Using various conventional gears, 1128 individuals (534 males and 594 females) have been collected. Total length (TL), standard length (SL), and body weight (BW) of each fish were measured. Ovaries were cautiously dissected, removed, and precisely weighed. TL ranges from 4.6 to 9.7 cm (BW = 0.7-9.27 g) for male and 4.6-10.3 cm (BW = 0.8-10.75 g) for female. Both male (47.34%) and female (52.66%) populations were the leading group in 7.00-7.99 cm TL. Overall SR was not notably altered from anticipated value of 1:1 (male:female = 1:1.11). Nonetheless, monthly variations of SR specified females were considerably outnumbered males in each month excluding March-May. Lm range was 6.4-7.0 cm, so larger than Lm is recommended to exploit. Monthly changes in GSI indicated that the main spawning season was from March to June. The spawning season was substantially correlated with rainfall, nonetheless with temperature. Additionally, relative weight indicated that habitat was imbalanced with higher predators. A fishing ban is recommended during peak spawning to protect L. guntea in the Payra River and its surroundings based on current research.

Chemodiversity of dissolved organic matter exports from subtropical humid catchment driven by hydrological connectivity.

The quantity and quality of dissolved organic matter (DOM) exported from source areas are closely related to hydrological linkage between source areas and streams, that is hydrological connectivity. However, understanding of how hydrological connectivity regulates the export of catchment DOM components remains inadequate. In this study, high-frequency monitoring of groundwater and runoff from subtropical humid catchment was conducted for 20 months, and hydrological connectivity was quantitatively characterized by considering both surface and subsurface hydrological processes. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was utilized to investigate the DOM molecular composition. Results showed that over half of the areas in the catchment could not persistently establish hydrological connectivity with the stream during the rainfall. The average proportion of lignin was the highest in DOM components, followed by tannin and proteins. Additionally, both modified aromaticity index and double bond equivalence reached maximums at peak discharge, reflecting terrestrial materials could increase DOM aromaticity and unsaturated degree. Partial least square-structural equation modeling revealed significantly direct effects of rainfall, antecedent conditions, and hydrological connectivity on dissolved organic carbon (DOC) export. Furthermore, nonlinear relationships were observed between hydrological connectivity and DOC, tannin, and condensed aromatics. Specifically, the instantaneous DOC flux increased dramatically when the hydrological connectivity strength exceeded 0.14; tannin and condensed aromatics exhibited a rapid increase with rising connectivity strength, but remained stable at connectivity strength above 0.25. However, hydrological connectivity showed no significant correlation with unstable components (such as lipids, protein, amino sugars, and carbohydrates). These results provide new insights into hydrological controls on the quantity and quality of DOM export and contribute to developing appropriate catchment management strategies for carbon storage.

Artificial Rainfall on Grain Quality and Baking Characteristics of Winter Wheat Cultivars in Korea.

Wheat (Triticum aestivum L.) stands as a significant cereal crop globally, including in Korea, where its consumption reached 35.7 kg per capita in 2023. In the southern regions of Korea, wheat cultivation follows paddy rice, with harvesting typically occurring during the rainy season in mid-June. This timing, coupled with the high humidity and unpredictable rainfall, often leads to pre-harvest sprouting and subsequent deterioration in flour quality. To assess the impact of rain on flour quality, an artificial rain treatment was administered 45 days after heading in an open field greenhouse, followed by flour quality analysis. The color measurement revealed an increase in the L* parameter, indicative of enhanced kernel vitreousness, attributed to endosperm starch degradation via alpha-amylase activation induced by water absorption. Moreover, significant changes were observed in ash content and the gluten index within the wetted group, resulting in decreased dough strength and stability, ultimately leading to a reduction in loaf volume. Consequently, it is recommended that wheat be harvested 4-7 days after reaching the physiological maturity stage to avoid the rainy season and ensure the production of high-quality wheat.

Ensemble machine learning using hydrometeorological information to improve modeling of quality parameter of raw water supplying treatment plants.

Source and raw water quality may deteriorate due to rainfall and river flow events that occur in watersheds. The effects on raw water quality are normally detected in drinking water treatment plants (DWTPs) with a time-lag after these events in the watersheds. Early warning systems (EWSs) in DWTPs require models with high accuracy in order to anticipate changes in raw water quality parameters. Ensemble machine learning (EML) techniques have recently been used for water quality modeling to improve accuracy and decrease variance in the outcomes. We used three decision-tree-based EML models (random forest [RF], gradient boosting [GB], and eXtreme Gradient Boosting [XGB]) to predict two critical parameters for DWTPs, raw water Turbidity and UV absorbance (UV254), using rainfall and river flow time series as predictors. When modeling raw water turbidity, the three EML models (rRF-Tu2=0.87, rGB-Tu2=0.80 and rXGB-Tu2=0.81) showed very good performance metrics. For raw water UV254, the three models (rRF-UV2=0.89, rGB-UV2=0.85 and rXGB-UV2=0.88) again showed very good performance metrics. Results from this study suggest that EML approaches could be used in EWSs to anticipate changes in the quality parameters of raw water and enhance decision-making in DWTPs.

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.

[Research progress on structure and hydrological processes in the karst critical zone of southwest China]. / è¥¿å—å–€æ–¯ç‰¹å ³é”®å¸¦ç»“æž„åŠå ¶æ°´æ–‡è¿‡ç¨‹ç ”ç©¶è¿›å±•.

The southwestern region of China is the largest exposed karst area in the world and serves as an important ecological security barrier for the upstream of Yangtze River and Pearl River. Different from the critical zone of non-karst areas, the epikarst, formed by an interwoven network of denudation pores, is the core area of karst critical zone. Water is the most active component that participates in internal material cycle and energy flow within the critical zone. We reviewed relevant research conducted in the southwestern region from three aspects: the characte-rization of critical zone structure, the hydrological processes of soil-epikarst system, and their model simulations. We further proposed potential research hotpots. The main approach involved multi-scale and multi-method integrated observations, as well as interdisciplinary collaboration. Precisely characterizing the eco-hydrological processes of the vegetation-soil-epikarst coupling system was a new trend in the future research. This review would provide scientific reference for further studies on hydrological processes in critical zones and regional hydrological water resource management in karst areas.

Investigation of pollutants accumulation in the submerged zone for pyrite-based bioretention facilities under continuous rainfall events.

Submerged zone in bioretention facilities for stormwater treatment has been approved to be an effective structure amendment to improve denitrification capability. However, the role and influence of water quality changes in the submerged zone under natural continuous random rainfall patterns are still not clear, especially when the rainfall is less than the pore water in the submerged zone. In this study, continuous rainfall events with different rainfall volume (light rain-light rain-heavy rain) were designed in a lab-scale woodchip mulched pyrite bioretention facility to test the effects of rainfall pattern. The results exhibited that light rain events significantly affected the pollutant removal performance of bioretention for the next rainfall. Different effects were observed during the long-term operation. In the 5th month, light rain reduced the ammonia removal efficiency of subsequent rainstorm events by 8.70%, while in the 12th month, when nitrate leakage occurred, light rain led to a 40.24% reduction in the next heavy rain event's nitrate removal efficiency. Additionally, light rain would also affect the concentration of by-products in the next rainfall. Following a light rain, the concentration of sulfate in the subsequent light rainfall can increase by 24.4 mg/L, and by 11.92 mg/L in a heavy rain. The water quality in the submerged zone and media characteristics analysis suggested that nitrogen conversion capacity of the substrate and microbes, such as Nitrospira (2.86%) and Thiobacillus (35.71%), as well as the in-situ accumulation of pollutants under light rain played important roles. This study clarifies the relationship between successive rainfall events and provides a more comprehensive understanding of bioretention facilities. This is beneficial for field study of bioretention facilities in the face of complex rainfall events.

Climate change impact and adaptation assessment for road drainage systems.

Climate change exhibits a clear trend of escalating frequency and intensity of extreme weather events, posing heightened risks to drainage systems along the existing road networks. However, very few studies to date have investigated the consequences of projected future changes in rainfall on main road drainage and the resulting risk of road flooding. The work presented in this paper builds on the limited research by introducing a probabilistic model for assessing the impact of climate change on road drainage systems, incorporating climate uncertainty and drainage system variation. The probabilistic scenario-based model and associated framework offer a practical and innovative method for estimating the impact of short-duration storms under future climates for 2071-2100, in the absence of fine-resolution spatio-temporal data. The model also facilitates the assessment of the effectiveness of a climate adaptation strategy. An illustrative case-study of a road drainage system located in the south of Ireland is presented. It was found that the probability of road flooding during intense rainfall is projected to surpass the current acceptable limits set by Irish standards. Assessment of a proactive climate adaptation strategy implemented in 2015 indicated it may need to be adjusted to further reduce climate change impacts and optimise adaptation costs.

Study on deformation and failure characteristics of oblique-cut locked rock slope under rainfall conditions.

Based on the disaster-pregnant environment and development characteristics of landslide disasters in the western region of Henan Province, a generalized model was established by taking the "oblique-cut" locking rock slope in the layered rock slope as the research object. The numerical simulation method was used to analyze the deformation and failure mechanism and stability influence law of the oblique-cut locking rock slope in western Henan under rainfall conditions. The results show that the inclination angle of the weak interlayer directly affects the deformation and failure characteristics of the slope rock mass. With the increase of the geometric parameters of the slope and the inclination angle of the weak interlayer, the failure mechanism is manifested as the slip shear failure along the level at the foot of the slope → the slip shear failure along the level at the foot of the slope (the sliding surface moves upward) → the shear failure in the middle of the slope surface → the slip shear failure along the level at the foot of the slope (the sliding surface moves downward) → the uplift shear failure at the lower edge of the rock layer. When the dip angle of the weak interlayer is constant, the slope stability decreases gradually with the increase in slope gradient and slope height, and the geometric factors of the slope control the overall change trend of the slope stability coefficient. When the slope is greater than 55° and the slope height is greater than 55 m, the shear stress of the slope locking section exceeds its shear strength, and the probability of landslide instability is greatly increased.

Perspectives on total phosphorus response in rivers: Examining the influence of rainfall extremes and post-dry rainfall.

Eutrophication is a significant environmental problem caused by nutrient loads from both point and non-point sources. Weather variables, particularly precipitation, affect the concentration of nutrients in water bodies, particularly those from non-point sources, in two contrasting ways. Heavy precipitation causes surface runoff which transports pollutants to rivers and increases nutrient concentration. Conversely, increased river flow can dilute the concentration, lowering it. This study investigates the impact of extreme precipitation, prolonged precipitation, and precipitation after a dry period on the total phosphorus concentration in the Moehne and Erft rivers in Germany, given the projected increase in frequency of extreme precipitation events and long drought periods due to climate change. The study comprises two parts: selecting extreme weather days from 2001 to 2021 and comparing observed Total Phosphorus concentrations with estimated concentrations derived from Generalized Additive Models and linear regression based on the discharge-concentration relationship. Changes in river TP concentration in response to continuous precipitation and precipitation after a dry period were also studied. Our results showed that during wet extreme and post-dry period rainfall events, TP concentration consistently surpassed expected values, underscoring the profound influence of intense rainfall on nutrient mobilization. However, we observed the impact of continuous rainfall to be non-unidirectional. Our work is distinguished by three key innovations: 1) addressing limitations in studying the effects of extreme weather on water quality due to limited temporal resolution, 2) incorporating both linear and non-linear modeling approaches for discharge-concentration relationships, and 3) performing a comprehensive analysis of temporal and spatial patterns of Total Phosphorus concentrations in response to varying rainfall patterns.

Comparative analysis of HEC-HMS and SWAT hydrological models for simulating the streamflow in sub-humid tropical region in India.

Assessment of water availability in sub-humid regions is important due to distinct climatic and environmental conditions. In this study, Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) models have been assessed in simulating streamflows in the sub-humid tropical Kabini basin in Kerala, India, spanning 1260 km2. Calibration and validation utilized daily weather data from 1997 to 2015 from the Muthankera gauging station. The study investigated the impact of routing methods on runoff simulation in the ArcSWAT, exploring Muskingum and Variable Storage methods. Evaluation metrics encompassed Nash-Sutcliffe Efïciency (NSE), Coefficient of Determination (R2), Percent bias (PBIAS), RMSE-observations standard deviation ratio (RSR), and Peak Percent Threshold Statistics (PPTS) approach for high-flow values. The result indicates that HEC-HMS outperforms SWAT concerning R2 and NSE values during daily calibration and validation. Monthly simulations showed HEC-HMS closely aligning with SWAT (Variable storage), outperforming SWAT (Muskingum). The PPTS approach proved effective in simulating high-flow values. Both models exhibited proficiency in streamflow analysis within the study area, promising predictive potential for future hydrological studies in sub-humid regions.

Observations of enhanced rainfall variability in Kenya, East Africa.

Understanding local patterns of rainfall variability is of great concern in East Africa, where agricultural productivity is dominantly rainfall dependent. However, East African rainfall climatology is influenced by numerous drivers operating at multiple scales, and local patterns of variability are not adequately understood. Here, we show evidence of substantial variability of local rainfall patterns between 1981 and 2021 at the national and county level in Kenya, East Africa. Results show anomalous patterns of both wetting and drying in both the long and short rainy seasons, with evidence of increased frequency of extreme wet and dry events through time. Observations also indicate that seasonal and intraseasonal variability increased significantly after 2013, coincident with diminished coherence between ENSO (El Nino Southern Oscillation) and rainfall. Increasing frequency and magnitude of rainfall variability suggests increasing need for local-level climate change adaptation strategies.