Molecular characteristics of dissolved organic phosphorus in watershed runoff: Coupled influences of land use and precipitation.

Land use and precipitation are two major factors affecting phosphorus (P) pollution of watershed runoff. However, molecular characterization of dissolved organic phosphorus (DOP) in runoff under the joint influences of land use and precipitation remains limited. This study used Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to study the molecular characteristics of DOP in a typical P-polluted watershed with spatially variable land use and precipitation. The results showed that low precipitation and intense human activity, including phosphate mining and associated industries, resulted in the accumulation of aliphatic DOP compounds in the upper reaches, characterized by low aromaticity and low biological stability. Higher precipitation and widespread agriculture in the middle and lower reaches resulted in highly unsaturated DOP compounds with high biological stability constituting a higher proportion, compared to in the upper reaches. While, under similar precipitation, more aliphatic DOP compounds characterized by lower aromaticity and higher saturation were enriched in the lower reaches due to more influence from urban runoff relative to the middle reaches. Photochemical and/or microbial processes did result in changes in the characteristics of DOP compounds during runoff processes due to the prevalence of low molecular weight and low O/C bioavailable aliphatic DOP molecules in the upper reaches, which were increasingly transformed into refractory compounds from the upper to middle reaches. The results of this study can increase the understanding of the joint impacts of land use and precipitation on DOP compounds in watershed runoff.

Temporal variation characteristics in the association between climate and vegetation in Northwest China.

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.

Characterising polycyclic aromatic hydrocarbons in road dusts and stormwater in urban environments.

The presence of polycyclic aromatic hydrocarbons (PAHs) pollution on urban road surfaces is one of the major environmental concerns. However, knowledge on the distribution variability of PAHs in road dusts (RDS) and stormwater is limited, which would restrict the further risk evaluation and mitigation implementation of PAHs in road stormwater runoff. This study collected RDS samples and stormwater samples on fourteen urban roads in Shenzhen, China. This study investigated the variation of sixteen PAHs species in RDS and stormwater, and further evaluated the intrinsic and extrinsic factors which influence PAHs accumulation on urban road surfaces. The research outcomes showed significant differences on spatial distribution of PAHs in RDS and in stormwater. The land use types, industrial, commercial and port areas and vehicular volume have a positive relationship with PAHs abundance while dust particle size showed a negative correlation with PAHs abundance. For two phases in stormwater, fluctuation of PAHs with the rainfall duration in total dissolved solid (TDS) was more intensive than in dissolved liquid phase (DLP). This indicated when PAHs attached to RDS enter stormwater, most of PAHs still tend to be on solid particles than in liquid. The study outcomes are expected to contribute to efficient designs of PAHs polluted stormwater mitigation.

Sustainable flood control strategies under extreme rainfall: Allocation of flood drainage rights in the middle and lower reaches of the yellow river based on a new decision-making framework.

Climate change has exacerbated the frequency and magnitude of extreme rainfall, which has led to the perpetuation of flooding as a hazard to humans and society. China has begun to consider introducing Flood drainage rights (FDR), a sustainable flood control measure, into non-engineering measures as a complement to engineering measures for flood control. FDR represent the right of regions to discharge regional floodwaters caused by extreme rainfall into the river, and are the primary means of controlling the amount of floodwaters from regions when regional flood capacity is exceeded. However, existing studies on quantitative FDR allocation still have limitations, and some previous methods have resulted in allocation schemes that are not entirely reasonable and fair because they do not comprehensively consider the influencing factors of FDR or the allocation method is unreasonable. This paper explores the impact of flooding on rural and agricultural areas. We incorporate the factors of agricultural economy and security and construct a system of the allocation indicators of FDR composed of five principles: Natural Environmental Endowment, General Economic and Social Development, Agricultural Economy and Security, Macro policy regulation, and Respect for Historical Background. Second, considering the influence of expert judgment and data of different time nodes on the allocation of FDR, we introduce the concepts of expert weight and time weight into the allocation model of FDR, and construct a new set of framework for the allocation of FDR, i.e., "[(expert weight + subjective weight)+(time weight + objective weight)]+decision making model ". To reduce the loss of information during the transformation of subjective judgments, we also introduced triangular fuzzy numbers for the transformation between expert judgments and numbers. Finally, we take the five provinces in the middle and lower reaches of the Yellow River as an example. Using the data from 2010 to 2021, we obtain the final allocation scheme (proportion) of FDR as Henan (33.26%) > Shaanxi (23.08%) > Inner Mongolia (21.31%) > Shanxi (14.44%) > Shandong (7.91%). On this basis, this paper utilizes sensitivity analysis and comparative validation to demonstrate the rationality and effectiveness of the method, and identifies several indicators that have a greater impact on the results of the allocation of FDR. FDR can form part of a set of integrated flood management system together with flood control projects, which greatly alleviates the drainage conflicts arising from flooding caused by extreme precipitation. Under extreme rainfall conditions, FDR improves drainage efficiency and minimizes the overall damage caused by flooding in the watershed. This study can contribute to the sustainable development of the watershed and provide a reference for the promotion and utilization of sustainable flood control measures.

Assessment of fine and coarse tyre wear particles along a highway stormwater system and in receiving waters: Occurrence and transport.

Tyre wear has been identified as a major road-related pollutant source, with road runoff transporting tyre wear particles (TWP) to adjacent soil, watercourses, or further through stormwater systems. The aim of this study was to investigate the occurrence and transport of TWP along a stormwater system. Water and sediment have been sampled at selected points (road runoff, gully pots, wells, outlet to a ditch, and stream) through a stormwater system situated along a highway in Sweden during November and December 2022, and March 2023. As there is limited data on the size distribution of TWP in different environmental media, especially in the size fraction <20 µm, the samples were fractioned into a fine (1.6-20 µm) and a coarse (1.6-500 µm) size fraction. The samples were analysed using a combination of marker compounds (benzene, α-methylstyrene, ethylstyrene, and butadiene trimer) for styrene-butadiene rubbers with PYR-GC/MS from which TWP concentration was calculated. Suspended solids were analysed in the water samples, and organic content was analysed in the sediment samples. TWP was found at nearly all locations, with concentrations up to 17 mg/L in the water samples and up to 40 mg/g in the sediment samples. In the sediment samples, TWP in the size fraction 1.6-20 µm represented a significant proportion (20-60%). Correlations were found between TWP concentration and suspended solids in the water samples (r = 0.87) and organic content in the sediment samples (r = 0.72). The results presented in this study demonstrate that TWP can be transported to the surrounding environment through road runoff, with limited retention in the studied stormwater system.

Variation of nitrate sources affected by precipitation with different intensities in groundwater in the piedmont plain area of alluvial-pluvial fan.

A substantial reservoir of nitrogen (N) in soil poses a threat to the quality and safety of shallow groundwater, especially under extreme precipitation that hastens nitrogen leaching into groundwater. However, the specific impact of varying precipitation intensities on the concentration and sources of nitrate (NO3-) in groundwater across diverse hydrogeological zones and land uses remains unclear. This study aims to elucidate the fluctuations in NO3- concentration, sources, and controlling factors in shallow groundwater under different intensities of precipitation (extreme heavy precipitation and continuous heavy precipitation) in a typical alluvial-pluvial fan of the North China Plain by using stable isotopes (δ2H-H2O, δ18O-H2O, δ15N-NO3-, δ18O-NO3-), hydrochemical analyses and the SIAR model. Affected by extreme heavy precipitation the depleted isotopes of δ2H-H2O and δ18O-H2O in groundwater of the entire area suggested the rapid recharge of fast flow by precipitation. The enriched isotopes of δ2H-H2O and δ18O-H2O of north part in alluvial fan after continuous heavy precipitation showed the recharge of translatory flow of soil water. NO3-concentrations increased to 78.9 mg/L after extreme heavy precipitation and increased to 105.3 mg/L after continuous heavy precipitation when compared to those in normal year (56.8 mg/L) of north part of the alluvial fan. However, NO3- concentrations had slight variation after continuous heavy precipitation of south part of the fan due to the deep vadose zone. The contribution ratio of sources of NO3- in groundwater by using SIAR analysis revealed manure & sewage (MS) as the primary NO3- source (accounting for 59.7-78.1%) before extreme heavy precipitation, chemical fertilizer (CF) making a minor contribution (6.9-17.3%). Different precipitation events and land use types lead to changes in NO3- sources. Affected by extreme heavy precipitation, the contribution of MS decreased while CF increased, particularly in vegetables (26.2-28.1%) and farmland (29.2-34.7%). After continuous heavy precipitation, MS increased again, particularly in vegetables (50.0%) and farmlands (20.4-66.4%), with CF either increasing or remaining steady. This indicated that continuous heavy precipitation accelerated the leaching of nitrogen (organic manure application) stored in deep soil to groundwater and it has a larger influence on the increasing of NO3- concentrations of groundwater than extreme heavy precipitation which carried nitrogen (chemical fertilizer application) in shallow soil to groundwater by fast flow. These findings underscore the importance of considering soil chemical N stores and their implications for groundwater contamination mitigation under future extreme climate scenarios, particularly in agricultural management practices.

Understanding Environmental Fate: Soil Variability and Rainfall Influence on Triafamone and Ethoxysulfuron Leaching.

Considering the environmental impact of triafamone and ethoxysulfuron, it is crucial to investigate their leaching behaviour under different geographical conditions. The present study evaluates the effects of application rate, soil properties and rainfall conditions on leaching of these herbicides and their metabolites. Ethoxysulfuron leached up to 50-60 cm with 82.95 to 89.23% detected in leachates while triafamone leached only to 10-20 cm and was < 0.01 µg mL-1 in leachates. Highest leachability was observed in loamy sand followed by sandy loam and clay loam soil. M1 metabolite (N-(2-((4,6-dimethoxy-1,3,5-triazin-2-yl) (hydroxy) methyl) -6-fluorophenyl) -1,1-difluoro-N-methyl methane sulfonamide) was majorly present in 0 to 10 cm soil depth. With increase in rainfall, downward mobility of both parent and M1 increased. Amendment of loamy sand soil with farmyard manure reduced the leachability indicating it could mitigate groundwater pollution. However, the effect of different exogenous OM amendments on leaching behaviour of herbicides needs to be evaluated.

Parameter Estimation Using the Inverse Problem Method for Simulating Lateral Inflow and Runoff Depth in a small catchment of Amazon.

The inverse problem method can be applied to determine the properties of hydrological phenomena and estimate the parameters, which cannot be measured directly. This type of inverse focus can facilitate the implementation of the kinematic wave model (direct model-DM), to fill gaps for lateral inflow rate and runoff depth in watersheds. Thus, the goal of the study was the application of the inverse problem method (IP). The lateral inflow rate was generally obtained as a Fourier transform to represent any watersheds. The study was developed using a small catchment in the Amazon where intense rainfall events occur, producing runoff and sediments, which affect rural populations. Lateral inflow rate and runoff depth were derived using precipitation data and parameters estimated through the KINEROS2 (K2)/direct model (DM) model and the ensuing solution methods with MCMC (Markov chains Monte Carlo)/Fourier transform. The developed method was applied to four rainfall-runoff events, leading to a good fit between the observed and predicted data (Nash-Sutcliffe coefficients between 0.76 and 0.85 and RMSE values between 1.80 mm and 6.72 mm).

Interspecific competition shapes bird species' distributions along tropical precipitation gradients.

The hypothesis that species' ranges are limited by interspecific competition has motivated decades of debate, but a general answer remains elusive. Here we test this hypothesis for lowland tropical birds by examining species' precipitation niche breadths. We focus on precipitation because it-not temperature-is the dominant climate variable that shapes the biota of the lowland tropics. We used 3.6 million fine-scale citizen science records from eBird to measure species' precipitation niche breadths in 19 different regions across the globe. Consistent with the predictions of the interspecific competition hypothesis, multiple lines of evidence show that species have narrower precipitation niches in regions with more species. This means species inhabit more specialized precipitation niches in species-rich regions. We predict this niche specialization should make tropical species in high diversity regions disproportionately vulnerable to changes in precipitation regimes; preliminary empirical evidence is consistent with this prediction.

Changes in productivity partitioning induced by precipitation extremes increase inaccuracy of grassland carbon estimation.

The fraction of net primary productivity (NPP) allocated to belowground organs (fBNPP) in grasslands is a critical parameter in global carbon cycle models; moreover, understanding the effect of precipitation changes on this parameter is vital to accurately estimating carbon sequestration in grassland ecosystems. However, how fBNPP responds to temporal precipitation changes along a gradient from extreme drought to extreme wetness, remains unclear, mainly due to the lack of long-term data of belowground net primary productivity (BNPP) and the fact that most precipitation experiments did not have a gradient from extreme drought to extreme wetness. Here, by conducting both a precipitation gradient experiment (100-500 mm) and a long-term observational study (34 years) in the Inner Mongolia grassland, we showed that fBNPP decreased linearly along the precipitation gradient from extreme drought to extreme wetness due to stronger responses in aboveground NPP to drought and wet conditions than those of BNPP. Our further meta-analysis in grasslands worldwide also indicated that fBNPP increased when precipitation decreased, and the vice versa. Such a consistent pattern of fBNPP response suggests that plants increase the belowground allocation with decreasing precipitation, while increase the aboveground allocation with increasing precipitation. Thus, the linearly decreasing response pattern in fBNPP should be incorporated into models that forecast carbon sequestration in grassland ecosystems; failure to do so will lead to underestimation of the carbon stock in drought years and overestimation of the carbon stock in wet years in grasslands.

Spatiotemporal variability identification and analysis for non-stationary climatic trends for a tropical river basin of India.

The non-stationary behavior of climatic variables has been increasingly recognized as a challenge that disrupts the equilibrium of human-defined climate-based stationary processes, including hydrological and agricultural practices, and irrigation systems. This study aims to investigate long-term trends and non-stationarity in climatic variables across 23 stations of the Krishna River basin, India. Prominent trends in rainfall, temperature, and their extreme indices were identified using the Modified Mann-Kendall (MMK), Bootstrapped Mann-Kendall (BMK), and Sen's Slope Estimator tests, while the Innovative Trend Analysis (ITA) test uncovered hidden trends and potential shifts in climatic patterns. This study addresses a critical research gap by exploring both significant and hidden trends in climatic variables, providing a better understanding of future dynamics. Traditional methods like MMK and Sen's Slope were insufficient to reveal these hidden trends, but ITA offered a more comprehensive analysis. The findings revealed an increase in total annual rainfall for almost 50% of the basin, which aligns with rising maximum temperatures, suggesting enhanced evaporation rates and subsequent fluctuations in rainfall patterns. Seasonal analysis indicated a shift towards decreased rainfall during winter and pre-monsoon seasons, contrasted by increased precipitation during the monsoon and post-monsoon periods, highlighting a clear alteration in rainfall distribution. The Simple Daily Intensity Index (SDII) and other indices suggest intensified rainfall events despite a decrease in the number of rainy days, indicating fewer but more intense events. Temperature analysis showed an overall increase in maximum temperatures, with the Diurnal Temperature Range (DTR) significantly increasing across all stations, implying greater daily temperature variations and potential for intensified water cycles and extreme climatic events. Furthermore, the study simplifies these trends by classifying them into two attributes: intensity and frequency, aiding policymakers in site-specific management of water resources and planning for future climatic scenarios. The presence of non-stationarity in extreme rainfall was confirmed by the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. These findings are significant as they conclude how climate change is altering hydrological patterns at each station. The study emphasizes the necessity for adaptive management strategies to mitigate the adverse impacts on agriculture, infrastructure, and human safety.

Model parameter estimation with imprecise information.

Model parameter estimation is a well-known inverse problem, as long as single-value point data are available as observations of system performance measurement. However, classical statistical methods, such as the minimization of an objective function or maximum likelihood, are no longer straightforward, when measurements are imprecise in nature. Typical examples of the latter include censored data and binary information. Here, we explore Approximate Bayesian Computation as a simple method to perform model parameter estimation with such imprecise information. We demonstrate the method for the example of a plain rainfall-runoff model and illustrate the advantages and shortcomings. Last, we outline the value of Shapley values to determine which type of observation contributes to the parameter estimation and which are of minor importance.

Integrated modeling of urban mobility, flood inundation, and sewer hydrodynamics processes to support resilience assessment of urban drainage systems.

With the increasing frequency of extreme weather events and a deepening understanding of disasters, resilience has received widespread attention in urban drainage systems. The studies on the resilience assessment of urban drainage systems are mostly indirect assessments that did not simulate human behavior affected by rainfall or semi-quantitative assessments that did not build simulation models, but few research characterizes the processes between people and infrastructure to assess resilience directly. Our study developed a dynamic model that integrates urban mobility, flood inundation, and sewer hydrodynamics processes. The model can simulate the impact of rainfall on people's mobility behavior and the full process including runoff generation, runoff entering pipes, node overflow, flood migration, urban mobility, and residential water usage. Then, we assessed the resilience of the urban drainage system under rainfall events from the perspectives of property loss and urban mobility. The study found that the average percentage increase in commuting time under different return periods of rainfall ranged from 6.4 to 203.9%. Calculating the annual expectation of property loss and traffic obstruction, the study found that the annual expectation loss in urban mobility is 9.1% of the annual expectation of property loss if the rainfall is near the morning commuting peak.

MODCEL-MHUS: a comprehensive multilayer hydrodynamic unified simulation for stormwater, sanitary sewer systems, and urban surface.

Numerous countries and regions have embraced implementing a separate sewer system, segregating sanitary and storm sewers into distinct systems. However, the functionality of these systems often needs to improve due to irregular interconnections, resulting in a mixed and malfunctioning system. Sewage collection is crucial for residential sanitation, but untreated collection significantly contributes to environmental degradation. Analyzing the simultaneous operation of both systems becomes vital for effective management. Using mathematical tools for precise and unified diagnosis and prognosis becomes imperative. However, municipal professionals and companies need more tools specifically designed to evaluate these systems in a unified way, mapping all the hydraulic connections observed in practice. This study proposes a unified simulation method for stormwater and sanitary sewer urban systems, addressing real-world scenarios and potential interferences. The primary goal is to develop a simulation method for both systems, considering system interconnections and urban layouts, involving hydrodynamic and water quality simulations. The practical application of this method, the Multilayer Hydrodynamic Simulation Method (MODCEL-MHUS), successfully identifies issues in urban water networks and suggests solutions, making it a valuable tool for urban water management and environmental engineering professionals.

Embracing epistemic uncertainty: a risk evaluation method for pollutants in stormwater.

In this study, we show that pollutants of emerging concern are, by nature, prone to the emergence of epistemic uncertainty. We also show that the current uncertainty quantification methods used for pollutant modelling rely almost exclusively on parameter uncertainty, which is not adequate to tackle epistemic uncertainty affecting the model structure. We, therefore, suggest a paradigm shift in the current pollutant modelling approaches by adding a term explicitly accounting for epistemic uncertainties. In a proof-of-concept, we use this approach to investigate the impact of epistemic uncertainty in the fluctuation of pollutants during wet-weather discharge (input information) on the distribution of mass of pollutants (output distributions). We found that the range of variability negatively impacts the tail of output distributions. The fluctuation time, associated with high covariance between discharge and concentration, is a major driver for the output distributions. Adapting to different levels of epistemic uncertainty, our approach helps to identify critical unknown information in the fluctuation of pollutant concentration. Such information can be used in a risk management context and to design smart monitoring campaigns.

Effect of simulated extreme rainfall on the vegetative phenology of perennial and annual herbaceous plants from a Brazilian dry forest.

Detecting changes in the phenological responses of herbaceous species as a function of predicted climate change is important for forecasting future scenarios for the functioning of dry tropical forests, especially when predicting an increase in the frequency and intensity of extreme droughts. Because of the sensitivity of plants to water availability, our study hypothesizes that if years become drier or wetter, herbaceous plants will synchronously change the onset, duration, and intensity of their vegetative phenophases. We used a historical series of 60 years of precipitation observations for the Caatinga vegetation to define daily average of precipitation for rainy (Twet), median (Tcontrol), and dry (Tdry) years. We simulated past average daily rainfall (Twet, Tcontrol, and Tdry) while growing two herbaceous perennials and two herbaceous annuals. We monitored plant growth and measured the activity (absence or presence) and intensity of vegetative phenophases. We used circular statistical analysis to assess differences between treatments. Our results revealed that leaf production was seasonal but relatively uniform for perennial species and highly seasonal (wet season) for annual species. Simulated dry years induced lower leaf emergence concentrated over a few months in annual species, but this effect was more strongly significant in one of the two perennial species. Both annual and perennial species can experience delayed and less intense leaf abscission during the rainy season in years with below-average precipitation. In contrast, large voluminous rains in years with above-average precipitation can accelerate and intensify the process of leaf renewal. If future precipitation reductions occur, the changes in phenological response indicate that the cover of annual and perennial herbaceous species in this study will likely decrease, altering the landscape and functioning of dry tropical forests. However, the potential trade-offs observed may help populations of these species to persist during years of severe drought in the Caatinga.

A spectrophotometric analysis of extracted water-soluble phenolic metabolites of lichens.

MAIN CONCLUSION: Rainwater most probably constitutes a relatively effective solvent for lichen substances in nature which have the potential to provide for human and environmental needs in the future. The aims were (i) to test the hypothesis on the potential solubility of lichen phenolic compounds using rainwater under conditions that partly reflect the natural environment and (ii) to propose new and effective methods for the water extraction of lichen substances. The results of spectrophotometric analyses of total phenolic metabolites in rainwater-based extracts from epigeic and epiphytic lichens, employing the Folin-Ciocalteu (F.-C.) method, are presented. The water solvent was tested at three pH levels: natural, 3, and 9. Extraction methods were undertaken from two perspectives: the partial imitation of natural environmental conditions and the potential use of extraction for economic purposes. From an ecological perspective, room-temperature water extraction ('cold' method) was used for 10-, 60-, and 120-min extraction periods. A variant of water extraction at analogous time intervals was an 'insolation' with a 100W light bulb to simulate the heat energy of the sun. For economic purposes, the water extraction method used the Soxhlet apparatus and its modified version, the 'tea-extraction' method ('hot' ones). The results showed that those extractions without an external heat source were almost ineffective, but insolation over 60- and 120-min periods proved to be more effective. Both tested 'hot' methods also proved to be effective, especially the 'tea-extraction' one. Generally, an increase in the concentration of phenolic compounds in water extracts resulted from an increasing solvent pH. The results show the probable involvement of lichen substances in biogeochemical processes in nature and their promising use for a variety of human necessities.

Satellite-based rainwater harvesting sites assessment for Dera Ghazi Khan, Punjab, Pakistan.

Water scarcity in arid regions poses significant livelihood challenges and necessitates proactive measures such as rainwater harvesting (RWH) systems. This study focuses on identifying RWH sites in Dera Ghazi Khan (DG Khan) district, which recently experienced severe water shortages. Given the difficulty of large-scale ground surveys, satellite remote sensing data and Geographic Information System (GIS) techniques were utilized. The Analytic Hierarchy Process (AHP) approach was employed for site selection, considering various criteria, including land use/land cover, precipitation, geological features, slope, and drainage. Landsat 8 OLI imagery, GPM satellite precipitation data, soil maps, and SRTM DEM were key inputs. Integrating these data layers in GIS facilitated the production of an RWH potential map for the region. The study identified 9 RWH check dams, 12 farm ponds, and 17 percolation tanks as suitable for mitigating water scarcity, particularly for irrigation and livestock consumption during dry periods. The research region was classified into four RWH zones based on suitability, with 9% deemed Very Good, 33% Good, 53% Poor, and 5% Very Poor for RWH projects. The generated suitability map is a valuable tool for hydrologists, decision-makers, and stakeholders in identifying RWH potential in arid regions, thereby ensuring water reliability, efficiency, and socio-economic considerations.

[Evolution of Water Quality and Characterization of Microbial Populations in Different Storage Forms of Roof Rainwater].

The safety and security of stored rainwater quality is the key to improve the efficiency of rainwater resources storage, and roof rainwater is the best scenario for rainwater storage and utilization. Through long-term monitoring of the evolution of water quality during the roof rainwater storage process, different storage materials （PE and glass） and different DO regulation modes （sealing and aeration） were constructed, and 16S rRNA microbial diversity sequencing and environmental factor correlation methods were used to characterize the changes in water quality under microbial metabolism during the rainwater storage process, as well as the potential risks of utilization and health. The results showed that the degradation of COD occurred mainly in the first 10 days of the storage process, and the nutrients were transformed mainly by microbial metabolism. There were differences in the characteristics of water quality changes under different water storage conditions, with traditional PE materials promoting the propagation of some pathogenic Xanthobacter, Alternaria, Stachybotrys, and Cladosporium, which were negatively correlated with DO and pH. Aeration was beneficial in reducing the abundance of bacteria and fungi, whereas the sealed water storage method was beneficial in inhibiting the growth of pathogenic bacteria such as Legionella.

Radon levels in Bengaluru during monsoon season.

A study on the dynamics of Radon and meteorological parameters was conducted in Bengaluru (12056'44'' N, 77030'25″ E, 840 m AMSL) during monsoon of 2014. All measured parameters exhibited a clear diurnal pattern, except for pressure, and are attributed to morning temperature inversion and afternoon enhanced vertical mixing. Concentration of Radon is higher during north eastern monsoon compared with south western monsoon and is due to the presence of continental air mass from north east of India. Monthly average Radon activity has exhibited a positive link with long wave radiation while displaying a negative correlation with ambient temperature, accumulated rainfall and soil temperature. During the study, ambient gamma dose rate of 190.8 nSv hour-1, shortwave radiation of 184.4 Wm-2, longwave radiation of -40.4 Wm-2, soil temperature (at 10 cm) of 26.3°C, humidity of 62.9%, pressure of 918.1 mbar and radon activity of 8.4 ± 0.5 Bq m-3 were recorded.