Changes In Precipitation Research Articles

Assessing seed pellet formulations to improve native plant restoration under water‐limited conditions

Water scarcity, a challenge expected to worsen with climate change, significantly hinders native plant community restoration. Enhancing seed‐based restoration requires methods to increase the water availability for seeds and seedlings. Surfactants and superabsorbent polymers (SAPs) can improve soil water‐holding capacity and infiltration, but their use in seed enhancements remains underexplored. We investigated whether pellets containing surfactants or SAPs could improve seedling emergence of two native species (Rytidosperma caespitosum and Chrysocephalum apiculatum) common in temperate grasslands in south‐eastern Australia under different watering treatments. We used a randomized block design with five watering treatments to simulate predicted changes in precipitation for south‐eastern Australia: ambient, two reducing overall water volume, and two reducing watering frequency while increasing watering volume to maintain ambient treatment water volume. We explored four enhanced pellets (two containing surfactants and two containing SAPs) and non‐pelleted seeds. Our results showed that watering events with larger volumes but reduced frequency increased seedling emergence. Under these conditions, block co‐polymer surfactants further increased seedling emergence of C. apiculatum, while synthetic SAP pellets promoted emergence of R. caespitosum. Block co‐polymer surfactants decreased R. caespitosum emergence, and both SAPs reduced C. apiculatum emergence under reduced watering frequency. A 50% reduction in overall water volume significantly reduced seedling emergence for both species, regardless of seed enhancement. These findings suggest that surfactants and SAP pellets can improve the success of seed‐based restoration under ambient conditions and when rainfall events are larger in volume but reduced in frequency, but not when the overall volume of rainfall is reduced.

Observed Retrogressive Thaw Slump Evolution in the Qilian Mountains

Climate warming can lead to permafrost degradation, potentially resulting in slope failures such as retrogressive thaw slumps (RTSs). The formation of and changes in RTSs could exacerbate the degradation of permafrost and the environment in general. The mechanisms of RTS progression and the potential consequences on the analogous freeze–thaw cycle are not well understood, owing partly to necessitating field work under harsh conditions and with high costs. Here, we used multi-source remote sensing and field surveys to quantify the changes in an RTS on Eboling Mountain in the Qilian Mountain Range in west-central China. Based on optical remote sensing and SBAS-InSAR measurements, we analyzed the RTS evolution and the underlying drivers, combined with meteorological observations. The RTS expanded from 56 m2 in 2015 to 4294 m2 in 2022, growing at a rate of 1300 m2/a to its maximum in 2018 and then decreasing. Changes in temperature and precipitation play a dominant role in the evolution of the RTS, and the extreme weather in 2016 may also be a primary contributor to the accelerated growth, with an average deformation of −8.3 mm during the thawing period, which decreased slope stability. The RTS evolved more actively during the thawing and early freezing process, with earthquakes having potentially contributed further to RTS evolution. We anticipate that the rate of RTS evolution is likely to increase in the coming years.

Temperature and precipitation changes under CMIP6 projections in the Mujib Basin, Jordan

Temperature and precipitation changes under CMIP6 projections in the Mujib Basin, Jordan

Observed changes in the climate and snow dynamics of the Third Pole

The Third Pole (TP) is the world’s largest highland and has one of the biggest reservoirs of glacier ice mass and snow cover on the Earth. Three major Asian rivers (the Indus, Ganga and Brahmaputra) are nourished by the melting of glaciers and snow in Central Himalaya, which are inevitable for the socioeconomic sustainability and water security of South Asia. Here, we investigate the long-term (1980–2020) changes in snow depth and precipitation in TP, where major precipitation occurs in the form of rainfall in summer, and snowfall in winter and spring. The seasonal mean snow depth is deep (≥1 m) in winter and shallow (≤0.2 m) in summer. The average snowmelt and snow water equivalent are higher in the central and western Himalaya and Karakoram ranges in spring, which are the regions with most glaciers in TP. There is a significant positive trend in total precipitation, about 0.01–0.03 mm d−1 yr−1 in the central and eastern TP during the South Asian Summer Monsoon for the 1980–2020 period. Snowmelt is also increasing (>0.5 × 10−3 mm yr−1) in the western Himalaya during spring, which is consistent with the temperature rise (0.04–0.06 °C yr−1) there. In addition, there is a notable increase in the annual mean glacier melt (here, the water equivalent thickness) in TP (−1 to −5 cm w.e. yr−1), with its highest values in the eastern and central Himalaya (−3 to −5 cm w.e. yr−1), as estimated for the period 2003–2020. On top of these, by the end of the 21st century, the Coupled Model Intercomparison Project Phase 6 (CMIP6) projections show that there would be a significant decrease in snow depth and an increase in temperature of TP in all shared socioeconomic pathways (SSPs). Henceforth, the increasing trend in temperature and melting of snow/glaciers in TP would be a serious threat to the regional climate, water security and livelihood of the people of South Asia.

Future Changes of Extreme Precipitation and Related Atmospheric Conditions in East Asia under Global Warming Projected in Large Ensemble Climate Prediction Data

Abstract Extreme precipitation is expected to pose a more severe threat to human society in the future. This work assessed the historical performance and future changes of extreme precipitation and related atmospheric conditions in a large ensemble climate prediction dataset, the database for Policy Decision-making for Future climate change (d4PDF), over East Asia. Compared with the TRMM and ERA5 datasets, the historical climate in d4PDF represents favorably the precipitation characteristics and the atmospheric conditions, although some differences are notable in the moisture, vertical motion, and cloud water fields. The future climate projection indicates that both the frequency and intensity of heavy precipitation events over East Asia increase compared with those in the present climate. However, when comparing the atmospheric conditions in the historical and future climates for the same precipitation intensity range, the future climate indicates smaller relatively humidity, weaker ascent, less cloud water content, and smaller temperature lapse rate, which negatively affect generating extreme precipitation events. The comparison of the precipitation intensity at the same amount of precipitable water between the historical and future climates indicates that extreme precipitation is weaker in the future, because of the more stabilized troposphere in the future. The general increase in extreme precipitation under future climate is primarily due to the enhanced increase in precipitable water in the higher temperature ranges, which counteracts the negative conditions of the stabilized troposphere.

SENSITIVITY OF THE KOLYMA RIVER RUNOFF TO MODERN CLIMATE CHANGE

The Kolyma River is a large river in the continuous permafrost zone. Its basin is subject to significant climatic changes. An information-modeling complex ECOMAG is employed for the study of water regime features and dynamics. ECOMAG calculates daily water flow rates at specified points based on meteorological data with a one-day resolution.This study analyzes the actual dynamics of water runoff and runoff-forming factors during the period from 1979 to 2013. A physical-mathematical model is adapted for the Kolyma River basin. Furthermore, the study examines the sensitivity of water regime characteristics to changing climate parameters. Calibration and verification demonstrated the ECOMAG’s ability to accurately reproduce observed water discharges for two points on the Kolyma River and the satisfactory performance on its tributary, the Bolshoy Anyui River. The ECOMAG model was for the first time employed for the Kolyma River basin, thus allowing the investigation of climate-related runoff changes. The preliminary statistical analysis revealed that if the average hydrological characteristics in the Kolyma River basin from 2000 to 2013 are compared with those from 1979 to 1999 a 5,1% rise of annual river runoff is evident for the Kolymskoye river section 283 km upstream the Kolyma River mouth (from 99,4 km3 in 1979-1999 up to 104,5 km3 in 2000-2013). The ECOMAG model also effectively captures changes in the annual water runoff and its intra-annual distribution.A rise in the mean annual air temperature by 1,3°C is characteristic of the modern time period. According to weather station data, the air temperature in March, April, November, and December increased by more than 2,5°C. The total annual precipitation increased by 8,3%, with September and March experiencing the most pronounced growth.To gain a more comprehensive understanding of the mechanisms governing the Kolyma River’s response to climate changes, the sensitivity of water runoff characteristics to air temperature and precipitation changes was analyzed using the ECOMAG model to generate artificial meteorological data series. The study demonstrates that water discharge is more sensitive to a 5% increase in precipitation than to a 1ºС rise in air temperature.

Does Urbanization Exacerbate Asymmetrical Changes in Precipitation at Divergent Time Scales in China?

AbstractUrbanization alters the thermal and dynamic environment of the local climate system, resulting in significant impacts on precipitation in both urban and adjacent areas. Nevertheless, there remains a significant gap in our understanding of urbanization‐induced effects on asymmetrical, symmetrical, and other precipitation patterns in urban agglomerations (UAs) with divergent background climates and geographic regions at different timescales. Specifically, this asymmetrical change pattern is characterized by an increase in heavy (or light) rainfall and a decrease in light (or heavy) rainfall. Here, we assessed the effects of urbanization on precipitation patterns across 18 UAs situated in diverse background climates and geographical areas in China at different timescales. The results demonstrate that urbanization predominantly alters precipitation patterns in UAs located in the humid region. Specifically, urbanization amplified asymmetrical changes in Yangtze River Delta, Pearl River Delta, Beibu Gulf, Middle Yangtze River, and Guanzhong, but exacerbated symmetrical changes in precipitation in some regions such as Chengdu‐Chongqing. Notably, the urbanization effect demonstrates greater significance at the hourly scale, as exemplified in the Yangtze River Delta, Pearl River Delta, and Middle Yangtze River, where the urban impact is nearly twice as pronounced when compared to the daily scale. Moreover, urbanization had either no effect or has a negative impact on precipitation patterns in UAs located within continental and arid regions. This is related to the intensity of urbanization, background climate and complex topography. This finding implies that urban managers should consider the impact of urbanization on precipitation patterns in different contexts to provide scientific guidance for urban planning.

Photosynthetic responses of switchgrass to light and CO2 under different precipitation treatments

AbstractSwitchgrass (Panicum virgatum L.) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO2 remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including −50%, −33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO2 concentration and light, we measured leaf net photosynthesis of switchgrass under different CO2 concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO2 response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO2 response curves. Precipitation change did not influence the maximum net photosynthetic rate (Pmax) but influenced other model parameters including quantum yield (α), convexity (θ), dark respiration (Rd), light compensation point (LCP), and saturated light point (LSP). Specifically, the mean Pmax of five precipitation treatments was 17.6 μmol CO2 m−2 s−1, and the ambient treatment tended to have a higher Pmax. The +33% treatment had the highest α, and the ambient treatment had lower θ and LCP, higher Rd, and relatively lower LSP. Furthermore, precipitation significantly influenced all model parameters of CO2 response. The ambient treatment had the highest Pmax, largest α, and lowest θ, Rd, and CO2 compensation point LCP. Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity.

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.

Do Tasmanian devil declines impact ecosystem function?

Tasmanian eucalypt forests are among the most carbon-dense in the world, but projected climate change could destabilize this critical carbon sink. While the impact of abiotic factors on forest ecosystem carbon dynamics have received considerable attention, biotic factors such as the input of animal scat are less understood. Tasmanian devils (Sarcophilus harrisii)-an osteophageous scavenger that can ingest and solubilize nutrients locked in bone material-may subsidize plant and microbial productivity by concentrating bioavailable nutrients (e.g., nitrogen and phosphorus) in scat latrines. However, dramatic declines in devil population densities, driven by the spread of a transmissible cancer, may have underappreciated consequences for soil organic carbon (SOC) storage and forest productivity by altering nutrient cycling. Here, we fuse experimental data and modeling to quantify and predict future changes to forest productivity and SOC under various climate and scat-quality futures. We find that devil scat significantly increases concentrations of nitrogen, ammonium, phosphorus, and phosphate in the soil and shifts soil microbial communities toward those dominated by r-selected (e.g., fast-growing) phyla. Further, under expected increases in temperature and changes in precipitation, devil scat inputs are projected to increase above- and below-ground net primary productivity and microbial biomass carbon through 2100. In contrast, when devil scat is replaced by lower-quality scat (e.g., from non-osteophageous scavengers and herbivores), forest carbon pools are likely to increase more slowly, or in some cases, decline. Together, our results suggest often overlooked biotic factors will interact with climate change to drive current and future carbon pool dynamics in Tasmanian forests.

Water addition but not reduction alters plant biomass-diversity relationship.

The relationship between plant aboveground biomass and diversity typically follows a unimodal pattern, showing a positive correlation in resource-poor habitats and a negative correlation in resource-rich environments. Precipitation is a crucial resource for both plant biomass and diversity in terrestrial ecosystems. However, the impact of precipitation changes on the relationship between plant biomass and diversity remains unclear. We conduct a water addition field experiment in a semiarid grassland and identify a unimodal relationship between plant biomass and species richness under ambient conditions. Water addition delays the declining phase of this unimodal curve and shift it upward compared to ambient conditions. Our meta-analysis of water addition experiments conducted across major biomes worldwide (grassland, shrubland, desert, and forest) supports this finding, while water reduction does not alter the biomass-diversity relationship. Water addition increases biomass in all climate but only increases species richness in arid and semiarid climate. Similarly, water reduction decreases biomass in all climate but only reduces species richness in arid and semiarid climate. Species richness in dry subhumid and humid climate does not change significantly. Furthermore, our field experiment shows that water addition increases plant diversity while decreasing soil inorganic nitrogen levels. The increase in one resource, such as water, leads to the scarcity of another, such as nutrient, thus postponing the declining phase of the plant biomass-diversity relationship typically observed in resource-rich habitats. Our research contributes to predicting the plant biomass-diversity relationship under changing precipitation conditions and highlights the complex interplay between water availability, nutrient level, and plant diversity.

Probabilistic projection of extreme precipitation changes over Iran by the CMIP6 multi-model ensemble

Probabilistic projection of extreme precipitation changes over Iran by the CMIP6 multi-model ensemble

Remote Sensing Methods and GIS Approaches for Carbon Sequestration Measurement: A General Review

Geospatial technologies like Remote Sensing (RS) and Geographic Information Systems (GIS) provide a platform for swiftly evaluating terrestrial Carbon Stock (CS) across extensive regions. Employing an integrated RS-GIS method for estimating Above-Ground Biomass (AGB) and precise carbon management emerges as a timely and economical strategy for implementing effective management plans on a localized and regional level. This study reviews different RS-related techniques utilized in CS assessment, particularly in arid lands, shedding light on the challenges, opportunities, and future trends associated with the process. As global warming poses adverse impacts on major ecosystems through temperature and precipitation changes, professionals have a call to develop evidence-based interventions to mitigate them. Carbon sequestration involves harnessing and storing carbon stocks from the atmosphere to minimize the adverse effects of climate change. The review explores the effectiveness of integrating remote sensing and GIS methodologies in quantifying carbon sequestration within agroforestry landscapes. In addition, this review also assesses the traditional methods, including their limitations, and deeply delves into recent techniques, emphasizing key remote sensing (RS) variables for biophysical predictions. This study showcases the efficacy of geospatial technologies in evaluating terrestrial carbon stock, particularly in arid regions. The study reviews diverse techniques and sensors, like optical Radio Detection and Ranging (RADAR), and Light Detection and Ranging (LiDAR), extensively employed for above-ground biomass (AGB) estimation and carbon stock assessment with RS data, introducing and discussing new methods. Existing literature was examined to present knowledge and evidence on the effectiveness of these technologies in carbon sequestration. The key findings of this review will inform future research and integration of technology, policy formulation, and carbon sequestration management to mitigate the impacts of climate change.

WITHDRAWN: Long-term warming and decreased precipitation regulated microbial community structure and potential function through enhanced predator-prey relationships in the Tibetan Plateau

Global climate change can shape the interactions among soil microbes and, in turn, mediate ecosystem functions. However, how these interactions were regulated remains to be investigated. This study utilized 16S rRNA, ITS, and 18S rRNA high-throughput sequencing to investigate the effects of simulated warming and precipitation changes on the major components of soil micro-food webs in the Qinghai-Tibetan Plateau through a field experiment. Adonis and non-metric multidimensional scaling (NMDS) analyses showed that compositions of bacteria, fungi and protists were all affected by changes in temperature and precipitation. Correlation and cross-trophic network analyses revealed that warming and decreased precipitation, both separately and together, enhanced the relationships between bacteria and protists, especially protistan predators. We found that the modified stochasticity ratio of the bacterial community assembly was best predicted by protists. The potential functional structures of bacteria were positively correlated with protistan predators under warming and decreased precipitation condition, suggesting enhanced predator-prey relationships between protists and bacteria might further influence the potential functional characteristics of bacterial communities. Our study indicated that climate change altered bacterial compositional and functional structure via enhanced predator-prey interactions. Therefore, in the context of global climate change, broader and more comprehensive studies on protist-regulated soil bacterial and fungal communities are imperative.

Dendroclimatology of Prosopis nigra in the Espinal woodlands, southeastern South America

This paper evaluates the dendrochronological potential of Prosopis nigra in the subtropical xerophytic forests of northeastern Argentina, an area of the Espinal forest particularly poor in dendrochronological records. Our study is based on tree-ring analyses of 23 cross sections providing a high-quality chronology (Rbar = 0.24 and EPS = 0.92). The mean annual radial increment recorded was 2.38 ± 1.51 mm. The inter-annual variability in the tree rings indicates that water availability from the previous winter to the current summer growing season is the major forcing on tree growth. Above-average rainfall and SPEI from July to February favored radial growth. Our results show for the first time the strong influence of both ENSO 3.4 and subtropical Atlantic SST variations, mediated by changes in local precipitation, on the growth of P. nigra in the Espinal. We concluded that P. nigra has great dendrochronological and dendroclimatological potential, since its rings are visible after careful polishing of the samples, and its inter-annual variations in radial growth are related to regional climate variability. These results can help improve our knowledge of the vulnerability of xerophytic forests to climate change in northeastern Argentina. In addition, this dendroclimatological study provides new proxy climate records for the Pampean grasslands, one of the most important food producing regions in the world.

Does Climate Change and Energy Consumption Affect the Food Security of European Union Countries? Empirical Evidence from a Panel Study

This study aims to provide empirical evidence on whether using renewable and non-renewable energy, CO2 emissions, and the resulting changes in temperature and precipitation can alter cereal yields in European Union countries. To this end, a panel data set covering 1992–2021 has been used to analyse the impact of climate change and economic factors on cereal production in European Union countries. The study employed various analytical techniques to better understand the impact of climate change and economic factors on cereal crop yields. These included using annual average temperature and rainfall to measure climate change, energy consumption, and economic growth to analyse the economic aspects. To achieve the objective, feasible generalised least squares (FGLS) models with robust standard errors and bootstrap and a quantile regression (QR) model with marginal analysis were employed. The Westerlund cointegration test confirmed the presence of cointegration between cereal production and climate variables, economic growth, and energy consumption. The results indicate that increases in temperature and precipitation may contribute to increased cereal production in European Union countries. In contrast, energy consumption, including renewable energy and CO2 emissions, may have a nonlinear effect on cereal production. Quantile regression analysis suggests climate change may impact crop yields most in countries with low and moderate cereal production per hectare. Increased CO2 emissions may increase yields in the initial period, but excessive CO2 may negatively impact cereal production in the long term. It would be advisable for countries with low and moderate crop productivity to consider implementing technological advances and combating global warming by modernising cultivation methods and making greater use of renewable energy sources.

How Volcanic Aerosols Globally Inhibit Precipitation

AbstractVolcanic aerosols reduce global mean precipitation in the years after major eruptions, yet the mechanisms that produce this response have not been rigorously identified. Volcanic aerosols alter the atmosphere's energy balance, with precipitation changes being one pathway by which the atmosphere acts to return toward equilibrium. By examining the atmosphere's energy budget in climate model simulations using radiative kernels, we explain the global precipitation reduction as largely a consequence of Earth's surface cooling in response to volcanic aerosols reflecting incoming sunlight. These aerosols also directly add energy to the atmosphere by absorbing outgoing longwave radiation, which is a major cause of precipitation decline in the first post‐eruption year. We additionally identify factors limiting the post‐eruption precipitation decline, and provide evidence that our results are robust across climate models.

Pyrethroid resistance distribution in Triatoma infestans and environmental association along the Argentine endemic zone

Insecticide resistance is considered a barrier to chemical control of Triatoma infestans, the main vector of Chagas disease in the Southern Cone of South America. Although initiatives to reduce the incidence of the disease in the region have integrated different strategies, they have mainly relied on vector elimination using pyrethroid insecticides such as deltamethrin. Reports of pyrethroid resistance in connection with T. infestans control failures first emerged in northern Argentina and southern Bolivia. Recently, a mosaic pyrethroid-resistant focus has been described in the center of the Argentine Gran Chaco (Department of General Güemes, Chaco Province), characterized by the presence of susceptible and very highly resistant populations in the same area. The involvement of different resistance mechanisms has been proposed, together with the contribution of environmental variables that promote the toxicological heterogeneity described. In the endemic zone of Argentina, however, new questions arise: Are there any other clusters of resistance? Is there a relationship between the distribution of resistance and environmental variables (as has been observed at smaller scale)? We studied toxicological data from insects collected and analyzed at 224 localities between 2010 and 2020 as part of the resistance monitoring conducted by the Chagas National Program. The sites were classified according to the survival rate of insects exposed to a discriminant dose of deltamethrin: 0–0.19 were considered susceptible, 0.2–0.79 low-resistance, and 0.8–1 high-resistance. Localities were georeferenced to describe the spatial distribution of resistance and to identify environmental variables (demographics, land use, urbanization, connectivity, and climate) potentially associated with resistance. We used Generalized Linear Models (GLMs) to examine the association between resistance and environmental predictors, selecting error distributions based on the response variable definition. For the entire period, 197 susceptible localities were distributed across the endemic zone. Localities with different survival rates were found throughout the area; 9 high-resistance localities circled the two previously identified resistant foci, and 18 low-resistance in 6 provinces, highlighting their relevance for control planning. Precipitation variables were linked to resistance in all the GLMs evaluated. Presence/absence models were the most accurate, with precipitation, distance from the capital city, and land use contributing to the distribution of resistance. This information could be valuable for improving T. infestans control strategies in future scenarios characterized by unpredictable changes in land use and precipitation.

Effective Storm Water Management in The Urban Area – A Case Study

Urbanization and climate change have negative effects on the changes of natural precipitation and runoff regime, which results with more frequent floods and landslides. Besides of the increased quantity of the stormwater that drainage channels have to collect, neg- ative consequences of urbanization are also evident through increased pollution of runoff stormwater. Stormwater has immense impacts on urban flooding and water quality, leaving the marginalized and the impoverished disproportionately impacted by and vulnerable to stormwater hazards. However, the environmental health concerns of socially and econom- ically marginalized individuals are largely underestimated. Therefore stormwater manage- ment should be adapted to these changes so that the negative effects of new hydrological conditions of precipitation and runoff and stormwater pollution in the urban areas are mitigated. By 2050 the world population will grow to about 9 billion contributing to deep changes in urban areas structure. This would increase the effect of water deficiency and along with projected climate changes the impact of urban flooding, urban heat islands or drought. Stormwater threats can be mitigated with the application of stormwater management meth- ods named differently such as ‘Sustainable (Urban) Drainage Systems’ (SUDS), ‘Low Impact Development’ (LID) or ‘Best Management Practices’ (BMPs). This method includes differ- ent techniques such as Green roof, Rain barrels and cisterns, Infiltration basin, Detention Ponds, Retention Ponds, Green walls, Porous pavements, Bioretention basins, Bioswales. The aim of the research includes a study of the effectiveness of urban stormwater manage- ment techniques for the case study area. The concept of urban stormwater management techniques refers to the ability to provide and manage this primary resource in quantitative and qualitative terms in order to satisfy the future needs of population. The storm wa- ter management techniques provides several benefits: mitigation of the urban heat island effects, reduction of air pollution, additionally, It induces important hydraulic advantages acting as an effective tool for reducing flood risk in urban area with runoff reduction, attenuation and delay of the peak flow. The results confirm that bioretention basin, Permeable pavement, Grassed swale, Infiltration basin are effective techniques for the reduction of total runoff volume of rainwater falling on their area.

A new scenario free procedure to determine flood peak changes in the Harz Mountains in response to climate change projections

Study areaSix catchments of different hydrological characteristics in the Harz Mountains, Germany. Study focusA new scenario free method for determining changes of flood peaks considering climate change is developed. Compared to existing methods, it accounts for heavy rainfall changes by a newly developed factor with two seasons and establishes a numerical relationship to a greater number of relevant climate predictors. For easier application, it is based on frequently available daily measurements. A functional test of the factor for heavy rainfall changes and its adjustment algorithm for the precipitation time series is performed. Using a regional AR5 ensemble, for the first time the error and the uncertainty of a new scenario free method are estimated and compared with an existing method. The new method is applied in the Harz Mountains, where the sensitivity of the region to different climate predictors is investigated. New hydrological insights for the regionThe adjusting algorithm for precipitation is able to adjust the time series while maintaining mass balance. The new method has a lower error than the reference method, with better matches of changes in the median of the climate ensemble as well as the most ensemble members. In general, the uncertainty of the seasonal results is below the climate uncertainty of the AR5 ensemble. Regarding future flood peaks, the regional catchments are most sensitive to mean precipitation changes, followed by heavy rainfall changes especially in the winter season. Mean temperature changes are of minor significance, but the catchments characteristics are important. The new method can be recommended for assessments of climate change impacts on floods in low to average mountain regions in Germany and Europe.