High Precipitation Events Research Articles

Soil Moisture Variations in Response to Precipitation Across Different Vegetation Types on the Northeastern Qinghai-Tibet Plateau.

An understanding of soil moisture conditions is crucial for hydrological modeling and hydrological processes. However, few studies have compared the differences between the dynamics of soil moisture content and soil moisture response to precipitation infiltration under different types of vegetation on the Qinghai-Tibet Plateau (QTP). In this study, a soil moisture sensor was used for continuous volumetric soil moisture measurements during 2015 and 2016, with the aim of exploring variations in soil moisture and its response to precipitation infiltration across two vegetation types (alpine meadow and alpine shrub). Our results showed that temporal variations in soil moisture at the surface (0–20 cm) and middle soil layers (40–60 cm) were consistent with precipitation patterns for both vegetation types. However, there was a clear lag in the soil moisture response to precipitation for the deep soil layers (80–100 cm). Soil moisture content was found to be significantly positively related to precipitation and negatively related to air temperature. Aboveground biomass was significantly negatively associated with the surface soil moisture content (0–20 cm) during the growing season. Statistically significant differences were observed between the soil water content of the surface, middle, and deep soil layers for the two vegetation types (p < 0.05). Soil moisture (19.81%) in the surface soil layer was significantly lower than that in the deep soil layer (24.75%) for alpine shrubs, and the opposite trend was observed for alpine meadows. The maximum infiltration depth of alpine shrubs was greater than that of alpine meadows under extremely high-precipitation events, which indicates that alpine shrubs might be less susceptible to surface runoff under extreme precipitation events. Furthermore, low precipitation amounts did not affect precipitation infiltration for either vegetation type, whereas the infiltration depth increased with precipitation for both vegetation types. Our results suggest that a series of small precipitation events may not have the same effect on soil moisture as a single large precipitation event that produces the equivalent total rainfall.

Geo-Hydrological Events and Temporal Trends in CAPE and TCWV over the Main Cities Facing the Mediterranean Sea in the Period 1979–2018

The Mediterranean region is regarded as the meeting point between Europe, Africa and the Middle East. Due to favourable climatic conditions, many civilizations have flourished here. Approximately, about half a billion people live in the Mediterranean region, which provides a key passage for trading between Europe and Asia. Belonging to the middle latitude zone, this region experiences high meteorological variability that is mostly induced by contrasting hot and cold air masses that generally come from the west. Due to such phenomenon, this region is subject to frequent intensive precipitation events. Besides, in this complex physiographic and orographic region, human activities have contributed to enhance the geo-hydrologic risk. Further, in terms of climate change, the Mediterranean is a hot spot, probably exposing it to future damaging events. In this framework, this research focuses on the analysis of precipitation related events recorded in the EM–DAT disasters database for the period 1979–2018. An increasing trend emerges in both event records and related deaths. Then a possible linkage with two meteorological variables was investigated. Significant trends were studied for CAPE (Convective Available Potential Energy) and TCWV (Total Column Water Vapor) data, as monthly means in 100 km2 cells for 18 major cities facing the Mediterranean Sea. The Mann–Kendall trend test, Sen’s slope estimation and the Hurst exponent estimation for the investigation of persistency in time series were applied. The research provides new evidence and quantification for the increasing trend of climate related disasters at the Mediterranean scale: recorded events in 1999–2018 are about four times the ones in 1979–1998. Besides, it relates this rise with the trend of two meteorological variables associated with high intensity precipitation events, which shows a statistically significative increasing trend in many of the analysed cities facing the Mediterranean Sea.

Spatial and agronomic assessment of water erosion on inland Pacific Northwest cereal grain cropland

The inland Pacific Northwest (PNW) is characterized by high erosion rates attributed to hilly topography, highly erodible silt loam soils, wet winter seasons with frequent freeze-thaw events, and widespread use of conventional tillage practices. Historically, annual water erosion from cropland in the region’s Palouse River basin averaged 20.6 t ha^-1, and more recent rates are 10, 13, and 11 t ha^-1 for the low (&lt;380 mm y^-1), intermediate (380 to 460 mm y^-1), and high (&gt;460 mm y^-1) precipitation zones. Identifying source areas for targeted, effective management requires understanding the factors affecting water erosion, especially how tillage practices and crop rotation interact in various topographic, soil, and climatic settings. The objectives of this study were to (1) understand how hillslope hydrological and water erosion processes are influenced by key environmental factors (soil, climate, and topography) and management practices (tillage and crop rotation), and (2) assess the spatial distribution of soil erosion at the county level and by precipitation zone over the last 30 years. We compiled various combinations of soil, climate, topography, tillage, and crop rotation, and simulated these combinations county by county with the Water Erosion Prediction Project (WEPP) model. Simulated average annual erosion rates were lowest in the low-precipitation zone and highest in the intermediate-precipitation zone, exceeding the USDA Natural Resources Conservation Service tolerable limit (11 t ha^-1) in many cases. Temporally, high precipitation events and fallow periods in the rotation greatly increase erosion. Average annual erosion rates in Whitman County are 13.6, 19.0, and 15.4 t ha^-1 in the three precipitation zones: low (&lt;380 mm y^-1), intermediate (380 to 460 mm y^-1), and high (&gt;460 mm y^-1), respectively. The intermediate-precipitation zone produced a total annual erosion of 4.2 × 10⁶ t, despite having the smallest area. Columbia County has the highest erosion rate with 23.7 t ha^-1 y^-1. Geospatial visualizations of the simulation results reveal critical source areas (“hotspots”) where estimated erosion rates are more than five times the average rates, providing crucial information for, and advancing our understanding of, targeting management and increasing efficiency of conservation practices.

Lagged Wetland CH4 Flux Response in a Historically Wet Year

AbstractWhile a stimulating effect of plant primary productivity on soil carbon dioxide (CO2) emissions has been well documented, links between gross primary productivity (GPP) and wetland methane (CH4) emissions are less well investigated. Determination of the influence of primary productivity on wetland CH4 emissions (FCH4) is complicated by confounding influences of water table level and temperature on CH4 production, which also vary seasonally. Here, we evaluate the link between preceding GPP and subsequent FCH4 at two fens in Wisconsin using eddy covariance flux towers, Lost Creek (US‐Los) and Allequash Creek (US‐ALQ). Both wetlands are mosaics of forested and shrub wetlands, with US‐Los being larger in scale and having a more open canopy. Co‐located sites with multi‐year observations of flux, hydrology, and meteorology provide an opportunity to measure and compare lag effects on FCH4 without interference due to differing climate. Daily average FCH4 from US‐Los reached a maximum of 47.7 ηmol CH4 m−2 s−1 during the study period, while US‐ALQ was more than double at 117.9 ηmol CH4 m−2 s−1. The lagged influence of GPP on temperature‐normalized FCH4 (Tair‐FCH4) was weaker and more delayed in a year with anomalously high precipitation than a following drier year at both sites. FCH4 at US‐ALQ was lower coincident with higher stream discharge in the wet year (2019), potentially due to soil gas flushing during high precipitation events and lower water temperatures. Better understanding of the lagged influence of GPP on FCH4 due to this study has implications for climate modeling and more accurate carbon budgeting.

Soil vulnerability index to climatic variability in coffee regions of Colombia

Global climate change is one of the main factors threatening agriculture. In this context, variations in precipitation have the strongest effect on soil fertility, plant nutrient availability, and erosion. This research aimed to assess soil vulnerability to climate variability in the central coffee-growing region of Colombia. This study analyzed soil components involved in the sustainability of the coffee production system as affected by extreme high and low precipitation events. For evaluation, three sensitivity indices were constructed, with a weighted aggregation structure and with weight values defined from expert knowledge. The indices were estimated by randomly selecting 432 coffee farms in the municipalities of Balboa and Santuario in Risaralda department and Salamina in Caldas department. The soil nutrient availability and conservation vulnerability index was moderate in the three municipalities (Balboa=2.87 and coefficient of variation-CV 13%; Santuario=2.88 and CV 10%; Salamina=2.9 and CV 9%). The soil leaching vulnerability index was very low in Balboa (4.33 and CV 3%) and Salamina (4.74 and CV 7%) and low in Santuario (3.57 and CV 19%). The soil loss vulnerability index was low in Balboa (3.32 and CV 10.03%) and Salamina (3.49 and CV 11.43%) and moderate in Santuario (3.13 and CV 9.34%). Lastly, the vulnerability of coffee-growing soil to climate variability was low in Balboa (3.33) and Salamina (3.45) and moderate in Santuario (3.09). Based on these results, in the three municipalities, coffee growers must introduce farming practices towards improving soil resilience and decreasing soil vulnerability to high and low precipitation extremes by adequately managing the sources and doses of fertilizers, soil conditioners, and compost and by implementing integrated management of weeds and litterfall.

Predicting Inflow Rate of the Soyang River Dam Using Deep Learning Techniques

The Soyang Dam, the largest multipurpose dam in Korea, faces water resource management challenges due to global warming. Global warming increases the duration and frequency of days with high temperatures and extreme precipitation events. Therefore, it is crucial to accurately predict the inflow rate for water resource management because it helps plan for flood, drought, and power generation in the Seoul metropolitan area. However, the lack of hydrological data for the Soyang River Dam causes a physical-based model to predict the inflow rate inaccurately. This study uses nearly 15 years of meteorological, dam, and weather warning data to overcome the lack of hydrological data and predict the inflow rate over two days. In addition, a sequence-to-sequence (Seq2Seq) mechanism combined with a bidirectional long short-term memory (LSTM) is developed to predict the inflow rate. The proposed model exhibits state-of-the-art prediction accuracy with root mean square error (RMSE) of 44.17 m3/s and 58.59 m3/s, mean absolute error (MAE) of 14.94 m3/s and 17.11 m3/s, and Nash–Sutcliffe efficiency (NSE) of 0.96 and 0.94, for forecasting first and second day, respectively.

Landscape-scale hydrologic response of plant invasion relative to native vegetation in urban forests

Large-scale invasion modifies watershed hydrology by changing surface runoff and lowering the seasonal availability of water to native plants. Due to costly field-based evapotranspiration (ET) measurements, which are highly localized and occasionally subject to instrument failure, landscape-scale water use assessments of invasive plants are infrequent. Therefore, the extent to which plant invaders alter water allocation between native and non-native vegetation in a given landscape is rarely assessed. We used a remote sensing-based ET modeling approach to measure the hydrologic response of an invasive shrub, Ligustrum sinense, across forests of the Charlotte Metropolitan Area, North Carolina. We hypothesized that this invader's widespread occurrence and dominant plant physiology significantly competes with native forests for water resources. We tested this hypothesis by comparing inter- and intra-annual variations in ET from invaded and uninvaded sites estimated using the surface-energy-balance system (SEBS) model and cloud-free Landsat images for the wettest (2003), driest (2007), and normal (2005 and 2011) water years. Our findings suggest that the water demand of L. sinense is higher than native forests (deciduous and evergreen) for most of the year except during the early spring and after high precipitation events. The daily ET flux of L. sinense was significantly different than evergreen vegetation during the driest year (2007) that, five years later (2011 - normal water year), was significantly different than both deciduous and evergreen vegetation types. This suggests that L. sinense consumes more water than native forest types, particularly during dry and normal precipitation years with increasing canopy cover over time making it a strong competitor with native vegetation for water resources in urban forests. Therefore, accounting for the hydrologic response of invasive plants and potential water savings from their removal from forests, particularly in water-scarce regions, may enable land managers and decision-makers to prioritize areas for monitoring and control efforts.

Stability of spatial dependence structure of extreme precipitation and the concurrent risk over a nested basin

Extreme low and high precipitation can cause natural disasters (e.g., drought and flood events) which have devastatingeffects on natural environment and the human society. In this study, we present a framework for assessing the stability of spatial dependence of extreme precipitation and their concurrence probability in a nested catchment. The Pearl River basin was used as a case study to test the applicability of the framework. This framework is threefold. This first part involves modeling spatial dependence of both summer maxima and winter minima precipitation between pairs of scattered gauges over the basin by employing the pair-copula constructions as a baseline model. The second part of this framework aims to identify the variability of spatial dependence as a result of the effects of external drivers. Specifically, variations in the spatial dependence of extreme precipitation in the Pearl River basin over different periods associated with the influence of large-scale climate signals were examined. The final part quantifies the probability of occurring extreme precipitation-related events simultaneously over broader areas related to a specific event at a given gauge and the possible spatial extents being affected. The results indicate that the presented framework is able to capture the large-scale spatial dependence structures of both summer maxima and winter minima precipitation. It also allows for explicitly estimating the pairwise concurrence probability of extreme high and low precipitation events and event-impacted areas across the basin.

Potato injury risk and weed control from reduced rates of PPO-inhibiting herbicides

AbstractThe ability to use the protoporphyrinogen oxidase (PPO)-inhibiting herbicides fomesafen, flumioxazin, and sulfentrazone in potato is limited regionally or by soil texture, largely because of crop injury noted in research in the 1990s. With that in mind, we evaluated whether reducing the herbicide rates could maintain weed control while providing more consistent crop safety. Studies were conducted on a silt loam and a coarse-textured loamy sand soil. Soil texture played a greater than anticipated role in PPO-inhibitor herbicide injury risk as it relates to high-precipitation events. For example, in 2020 at the silt loam location, there were five precipitation events across the season that exceeded 2.5 cm, including one 6 d after treatment (DAT), and a seasonal total precipitation that was over 10 cm greater than the previous year. Despite excessive moisture and initial potato injury as high as 27% where flumioxazin was applied at the high rate with S-metolachlor, by 29 DAT injury was less than 10% in all treatments, and marketable tuber yield was similar among treatments. In contrast, in 2020 at the loamy sand location, there were four precipitation events across the season that exceeded 2.5 cm, and potato injury was as much as 60%. In 2020 the high amount of injury from flumioxazin was hypothesized to be caused by precipitation before herbicide application and not after, suggesting a need for more research in this area. This work documents the fine line between yield reduction presumably caused by reduced weed control and yield reduction assumed to be related to herbicide injury. This delineation between adequate weed control and consistent crop safety may differ by soil texture and environmental conditions, supporting the notion that custom-tailored weed management may become more necessary as high-precipitation events become more common in upper midwestern U.S. agricultural systems.

Historical Changes and Future Projections of Extreme Temperature and Precipitation along the Sichuan-Tibet Railway

Based on multiresource high-resolution in situ and satellite merged observations along with model simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), this paper first investigated historical changes in extreme temperature and precipitation during the period of 1979–2018 in areas along the Sichuan–Tibet Railway, and then projected the future changes in the frequency and intensity of extreme temperature and precipitation under the representative concentration pathways (RCPs) of the RCP 4.5 and 8.5 scenarios. This study is expected to enhance our understanding of the spatiotemporal variability in the extreme temperature and precipitation along the Sichuan–Tibet Railway, and to provide scientific basis to advance the Sichuan–Tibet Railway construction and operation. The results show that temperatures in the Sichuan–Tibet region have shown a noticeable warming trend in the past 40 years, and the increase of minimum temperature is significantly higher than that of maximum temperature in the northwest of the region. The significant increase of precipitation is mainly distributed in the northwest of the Tibetan Plateau, and there is no significant change in precipitation in other areas along the Sichuan–Tibet Railway, except in Lhasa and its surrounding areas. However, precipitation along the Sichuan–Tibet Railway has shown a remarkable decrease in the past 20 yr. The warm days and nights have clearly increased by 6 and 5 day decade−1 for 1979–2019, while cold days and nights have markedly decreased by about 6.6 and 3.6 day decade−1, respectively. In the past 20 yr, the areas with increased precipitation from very wet days and extremely wet days are mainly distributed to the north of the Sichuan–Tibet Railway, while in the areas along the railway itself the very wet days and extremely wet days are decreasing. Under the RCP 4.5 and 8.5, the temperature in the Sichuan–Tibet region will increase significantly, and the frequency of extreme high (low) temperature events in the late 21st century (2070–2099) will greatly increase (decrease) by about 50%–80% (10%) compared with occurrences in the late 20th century (1970–1999). Meanwhile, the frequency of very wet days and extremely wet days in the Sichuan–Tibet region will increase by ~2%–19% and 2%–5%, respectively, and the areas along the Sichuan–Tibet Railway will be affected by more extreme high temperature and extreme precipitation events.

Hydrological Analysis of Extreme Rain Events in a Medium-Sized Basin

The hydrological response of a medium-sized watershed with both rural and urban characteristics was investigated through event-based modeling. Different meteorological event conditions were examined, such as events of high precipitation intensity, double hydrological peak, and mainly normal to wet antecedent moisture conditions. Analysis of the hydrometric features of the precipitation events was conducted by comparing the different rainfall time intervals, the total volume of water, and the precedent soil moisture. Parameter model calibration and validation were performed for rainfall events under similar conditions, examined in pairs, in order to verify two hydrological models, the lumped HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System model) and the semi-distributed HBV-light (a recent version of Hydrologiska Byråns Vattenbalansavdelning model), at the exit of six individual gauged sub-basins. Model verification was achieved by using the Nash–Sutcliffe efficiency and volume error index. Different time of concentration (Tc) formulas are better applied to the sub-watersheds with respect to the dominant land uses, classifying the Tc among the most sensitive parameters that influence the time of appearance and the magnitude of the peak modeled flow through the HEC-HMS model. The maximum water content of the soil box (FC) affects most the peak flow via the HBV-light model, whereas the MAXBAS parameter has the greatest effect on the displayed time of peak discharge. The modeling results show that the HBV-light performed better in the events that had less precipitation volume compared to their pairs. The event with the higher total precipitated water produced better results with the HEC-HMS model, whereas the rest of the two high precipitation events performed satisfactorily with both models. April to July is a flood hazard period that will be worsened with the effect of climate change. The suggested calibrated parameters for severe precipitation events can be used for the prediction of future events with similar features. The above results can be used in the water resources management of the basin.

The role of superficial geology in controlling groundwater recharge in the weathered crystalline basement of semi-arid Tanzania

Study regionLittle Kinyasungwe River Catchment, central semi-arid Tanzania. Study focusThe structure and hydraulic properties of superficial geology can play a crucial role in controlling groundwater recharge in drylands. However, the pathways by which groundwater recharge occurs and their sensitivity to environmental change remain poorly resolved. Geophysical surveys using Electrical Resistivity Tomography (ERT) were conducted in the study region and used to delineate shallow subsurface stratigraphy in conjunction with borehole logs. Based on these results, a series of local-scale conceptual hydrogeological models was produced and collated to generate a 3D conceptual model of groundwater recharge to the wellfield. New hydrological insights for the regionWe propose that configurations of superficial geology control groundwater recharge in dryland settings as follows: 1) superficial sand deposits act as collectors and stores that slowly feed recharge into zones of active faulting; 2) these fault zones provide permeable pathways enabling greater recharge to occur; 3) ‘windows’ within layers of smectitic clay that underlie ephemeral streams may provide pathways for focused recharge via transmission losses; and 4) overbank flooding during high intensity precipitation events increases the probability of activating such permeable pathways. These conceptual models provide a physical basis to improve numerical models of groundwater recharge in drylands, and a conceptual framework to evaluate strategies (e.g., Managed Aquifer Recharge) to artificially enhance the availability of groundwater resources in these regions.

High-resolution records of anthropogenic activity and geohazards from the reservoir of Sun Moon Lake, Central Taiwan

Sun Moon Lake is the first dam reservoir constructed in Taiwan with the capability of generating hydroelectricity satisfying the whole Taiwan need during the Japanese colonial period since 1934 CE. Now, the Sun Moon Lake is one of the biggest hydropower stations in Taiwan and has become an important touring area. During World War II (1944–1945 CE), the hydroelectric power plant at Sun Moon Lake was bombed by the U.S. air force, which caused severe damage to the dam structure. More recently, the dam structure was also damaged during the 1999 CE Chi-Chi earthquake whose epicenter is nearby in the Nantou County. A suite of cores were taken from both Sun Lake and Moon Lake, and two selected cores, Sun 2–1 and SM 16 4–3, from Sun Lake were detailed studied with multiple analyses, including X-ray imaging, magnetic susceptibility, visible spectrophotometry, X-ray fluorescence (XRF) scanning, and mineral analysis. We discovered that the increase of Ca content in the sediments not only clearly indicates when the dam was constructed at Sun Moon Lake but also records evidence of structure repairs after both the World War II bombing and the Chi-Chi earthquake. Additionally, the yellow turbidite, X-ray image, and low-Ca signals in Core Sun 2–1 strongly correlate to the typhoon events that caused severe floods in the watershed of Zhuoshui River. The turbidite layers caused by the 1963 Gloria Typhoon are also characterized by conspicuous high peak of Fe/Mn in both cores. This study shows that XRF scanning results are useful for recognition of human activity and for high precipitation event correlation. Moreover, the appearance of charcoal layers shows evidence of forest burning and slash-and-burn activities by humans during the past 4,000 years back to the Middle Neolithic Age.

Sensitivity of productivity to precipitation amount and pattern varies by topographic position in a semiarid grassland

AbstractAboveground net primary productivity (ANPP) in grasslands is an important integrator of terrestrial ecosystem function, a key driver of global biogeochemical cycles, and a critical source of food for wild and domesticated herbivores. ANPP exhibits high spatial and temporal variability, driven by a suite of factors including precipitation amount and pattern, biotic and abiotic legacies, and topographic heterogeneity. Global climate models forecast an altered hydrological cycle due to climate change, including higher precipitation variability and more extreme events, which may further increase spatiotemporal variability in ANPP. Therefore, it is essential to understand the sensitivity of this central ecosystem function to various precipitation metrics, legacies, and topographic positions to better inform sustainable grassland management. In this study, we analyzed long‐term (36‐yr) ANPP data collected across a topographic sequence in the semiarid shortgrass steppe of North America to examine patterns and drivers of spatiotemporal variability in ANPP. We observed that (1) ANPP varied substantially by topographic position, with greater divergence during years with high production, (2) ANPP variability was higher temporally (16‐fold maximum difference across years) than spatially (4‐fold maximum difference across topographic positions), (3) warm‐season perennial grasses were the dominant plant functional type across all topographic positions and strongly influenced total ANPP dynamics, and (4) ANPP had strong sensitivities to current year precipitation amount and pattern that varied by plant functional type, as well as weaker sensitivities to precipitation and productivity legacies. Overall, the lowest topographic position had the highest sensitivity to precipitation, likely due to higher resource availability via the downhill movement of water and nutrients during years with high precipitation and large rainfall events. These results suggest that temporal and spatial ANPP variability in shortgrass steppe is primarily driven by the combined effects of precipitation amount and pattern during the current year, with the dominant warm‐season perennial grasses governing these responses.

Skill assessment of TIGGE precipitation forecasts in the four basins of Iran

In atmospheric sciences, forecast assessment, the process of examining the quality of forecasts, is very important. For this reason, we carried out a comprehensive evaluation of the most important global numerical weather forecast (NWP) models for the Iranian basins of Karkheh, Karun, Urmia, and Sefidrood. This study aims to evaluate the output of six different NWP models from the TIGGE database in important basins of Iran, to determine the most appropriate model for each basin. The assessment period took place between 2008 and 2018 and evaluated probabilistic and non-probabilistic methods. In the Karun Basin, the global NWP models were shown to perform better than in the other three basins. Overall, the UKMO (United Kingdom Met Office) and ECMWF (European Medium-Range Weather Forecast) performed best, while the Korean Meteorological Administration (KMA) showed the poorest performance among the models in the four basins. In the 25 mm threshold, most models underestimated precipitation events. The ECMWF model showed reliable and sharp forecasts and was better able to discriminate between low, medium, and high precipitation events compared to other models. Compared to those of other models, the UKMO model demonstrated greater brier skill scores. In general, the ECMWF, UKMO, ECCC (Environment and Climate Change Canada), and National Center for Environmental Forecast (NCEP) models performed relatively satisfactory in all four basins, although they forecasted better in basins with higher mean precipitation. These models are recommended for flood warning systems, and water resource decision making in Iran. However, all forecasts will need post-processing for operational applications.

Changes of extreme high temperature and heavy precipitation in the Guangdong-Hong Kong-Macao Greater Bay Area

The changes of extreme high temperature and heavy precipitation events in the Guangdong-Hong Kong-Macao Greater Bay Area from 1961 to 2019 are analyzed in this paper. Based on the high-resolution climate projection simulations, this study also projects the future risks of heat and flood disasters. The results indicate that hot days, hot nights, heat wave durations, extreme daily maximum and minimum temperature have increased significantly at the rates of 3.6 d/10a, 6.0 d/10a, 2.1 d/10a, 0.23 °C/10a and 0.21 °C/10a, respectively. The heavy and very heavy precipitation days, extreme precipitation amount, maximum 1-day and 5-day precipitation amount have increased by 0.6 days, 0.2 days, 12.5 mm, 0.7 mm and 3.5 mm per 10 years, respectively. All the extreme indices will keep increase at similar rates. In the mid-21st, the area with highest heat and flood risks shows an increase by a factor of 10, mainly located in Guangzhou, Foshan, Dongguan, Shenzhen, Hong Kong and the northern part of Zhongshan. The area proportions of the highest two risk levels of heat and flood disasters will be as high as 66% and 60%, respectively. Considering both high climate risks and urbanization developments, it is necessary to improve the resistance to extremes and enhance the resilience of society to these extreme disasters.

Using logistic regression to model the risk of sewer overflows triggered by compound flooding with application to sea level rise

Coastal wastewater and storm water systems can be overwhelmed during high precipitation events, particularly when compounded by high storm surge that blocks spillways and drainage ways. Sea level rise (SLR) brings increased risk of such compound flooding events, triggering sanitary sewer overflows (SSO) which release waste water into the local environment. A logistic regression model was developed to better predict this risk in southern Pinellas County, FL. Model variables were selected from 2000 to 2017 cumulative precipitation and coastal water levels using both objective and subjective criteria. The 2 day (P2) and 90 day (P90) cumulative precipitation, and 2 day water level maximum (W2) were identified as significant predictors from the p-value of their model coefficients, but required an interaction term P2*W2 for model fidelity. The model correctly hindcasted all 6 identified SSOs from 2000 to 2017. SLR was represented by a range of values up to 0.5 m added to W2. For a SLR of 0.5 m the number of SSO days increased by a factor of 42–52 and the number of individual events increased by a factor of ~15. Subtracting recent SLR from W2 reduced the probability of some recent events, suggesting that SLR already is increasing the rate of SSOs.

Aerosol-enhanced high precipitation events near the Himalayan foothills

Abstract. Particulate emissions can alter the physical and dynamical properties of cloud systems and, in turn, amplify rainfall events over orographic regions downwind of highly polluted urban areas. The Indo-Gangetic Plain, one of the most polluted regions of the world, is located upwind of the Himalayan foothills. The region, therefore, provides an opportunity for studying how aerosol effects, in connection with orographic forcing, affect extreme rainfall events. This study uses 17 years (2001–2017) of observed rain rate, aerosol optical depth (AOD), meteorological reanalysis fields and outgoing long-wave radiation to investigate high precipitation events on the foothills of the Himalayas. Composite analysis of all these co-located data sets for high precipitation events (daily rainfall &gt; 95th percentile) is done to understand the inherent dynamics and linkages between the AOD and extreme events. Clear and robust associations are found between high precipitation events, high aerosol loading and high moist static energy values. Results show an average increase in AOD by 36 %, along with an average increase in low-level moist static energy (1000–850 hPa) by ≈ 1500 J kg−1 inside the selected domain for high precipitation events. The finding highlights the crucial role of the aerosol direct radiative effect on high precipitation events over the Himalayan region.

Assessment of Extremes in Global Precipitation Products: How Reliable Are They?

AbstractGlobal gridded precipitation products have proven essential for many applications ranging from hydrological modeling and climate model validation to natural hazard risk assessment. They provide a global picture of how precipitation varies across time and space, specifically in regions where ground-based observations are scarce. While the application of global precipitation products has become widespread, there is limited knowledge on how well these products represent the magnitude and frequency of extreme precipitation—the key features in triggering flood hazards. Here, five global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR, and WFDEI) are compared to each other and to surface observations. The spatial variability of relatively high precipitation events (tail heaviness) and the resulting discrepancy among datasets in the predicted precipitation return levels were evaluated for the time period 1979–2017. The analysis shows that 1) these products do not provide a consistent representation of the behavior of extremes as quantified by the tail heaviness, 2) there is strong spatial variability in the tail index, 3) the spatial patterns of the tail heaviness generally match the Köppen–Geiger climate classification, and 4) the predicted return levels for 100 and 1000 years differ significantly among the gridded products. More generally, our findings reveal shortcomings of global precipitation products in representing extremes and highlight that there is no single global product that performs best for all regions and climates.

Protecting rivers by integrating supply-wastewater infrastructure planning and coordinating operational decisions

Placing water quality in rivers at the centre of water infrastructure planning and management is an important objective. In response there has been a range of ‘whole system’ analyses. Few studies, however, consider both abstraction (water removed from rivers) and discharge (water returned) to inform the future planning of water systems. In this work we present a systems approach to analysing future water planning options where system development prioritises the water quality of the receiving river. We provide a theoretical demonstration by integrating water supply and wastewater infrastructure, and downstream river water quality, on an open-source, stylised, systems model for London, UK, at a citywide scale. We show that models which consider either supply or wastewater separately will underestimate impacts of effluent on the water quality, in some cases by amounts that would require £1 billion worth of infrastructure equivalent to mitigate. We highlight the utility of the systems approach in evaluating integrated water infrastructure planning using both socio-economic and environmental indicators. Through this approach we find unintended impacts from planning options on downstream river quality; including benefits from water demand management and rainwater harvesting, and costs from wastewater reuse. Finally, we present a novel management planning option between supply and wastewater, which we refer to as ion-Effluent Dilution (AED), that is, to reduce river abstractions during high precipitation events to dilute untreated sewer spills. The AED option is found to provide up to £200 million worth of equivalent infrastructure in river quality improvements and has minimal impact on the reliability of water supply while requiring only a change in operational decision making. This proof-of-concept study highlights that seeing our water systems differently with this holistic approach could fundamentally change the way we think about future water infrastructure planning so that it works both for people and the environment.