Increase In Extreme Rainfall Events Research Articles

Application of Capillary Barrier Systems for Slope Stabilization Under Extreme Rainfall: A Case Study of National Highway 10, India

Global warming has led to an increase in extreme rainfall events, which often result in landslides, posing significant threats to infrastructure and human life. This study evaluated the effectiveness of the Capillary Barrier System (CBS) in enhancing slope stability along a vulnerable section of India’s National Highway 10 (NH10) during maximum daily rainfall. The GEOtop model was employed to conduct water balance simulations and obtain the pore–water pressure (PWP), which was then used to calculate the Factor of Safety (FoS). Results showed that CBS effectively delayed the rise in PWP, leading to lower peak values and smaller areas of very high and high risk levels. Spatial distribution mapping further confirmed that CBS minimized very high risk zones. At three historical landslide points, CBS slopes generally maintained FoS values above 1, demonstrating enhanced stability and improved resilience to extreme rainfall. These findings highlight the potential of CBS as a viable strategy for slope reinforcement in regions susceptible to heavy rainfall.

Optimize Stormwater Management for Green Roofs Based on IoT Technology and Sensor Networks

The intensification of global climate change and the significant increase of extreme rainfall events have made traditional urban drainage systems face great adjustments. As a key component of green infrastructure to avoid urban flood risk, green roofs are receiving increasing attention due to their unique capabilities in stormwater management. This paper explores the potential of Internet of Things (IoT) technology and sensor networks to enhance green roof stormwater management. Integrated real-time monitoring of key environmental parameters, including soil moisture, temperature and rainfall, enables the system to dynamically adjust roof drainage and irrigation strategies. This greatly improves the rainwater retention capacity and reduces the pressure on the municipal sewage system. The results show that the combination of IoT technology and sensor networks not only improves the efficiency of green roof management in combating climate change, but also promotes the efficient use of water resources and enhances the adaptability and sustainability of the system. This research provides the necessary technical support for the wider adoption of green roofs in urban environments and offers viable solutions to future challenges posed by climate change.

Effectiveness of wetlands as reservoirs for integrated water resource management in the Ruzizi plain based on water evaluation and planning (WEAP) approach for a climate-resilient future in eastern D.R. Congo

It is widely predicted that climate change’s adverse effects will intensify in the future, and along with inadequate agricultural practices, settlement development, and other anthropic activities, could contribute to rapid wetland degradation and thus exert significant negative effects on local communities. This study sought to develop an approach based on the Integrated Water Resource Management (IWRM) in the Ruzizi Plain, eastern Democratic Republic of Congo (DRC), where adverse effects of the climate change are increasingly recurrent. Initially, we analyzed the trends of climate data for the last three decades (1990–2022). Subsequently, the Water Evaluation and Planning (WEAP) approach was employed on two contrasting watersheds to estimate current and future water demands in the region and how local wetlands could serve as reservoirs to meeting water demands. Results indicate that the Ruzizi Plain is facing escalating water challenges owing to climate change, rapid population growth, and evolving land-use patterns. These factors are expected to affect water quality and quantity, and thus, increase pressure on wetland ecosystems. The analysis of past data shows recurrence of dry years (SPI ≤ − 1.5), reduced daily low-intensity rainfall (Pmm < 10 mm), and a significant increase in extreme rainfall events (Pmm ≥ 25 mm). The WEAP outcomes revealed significant variations in future water availability, demand, and potential stressors across watersheds. Cropland and livestock are the main water consumers in rural wetlands, while households, cropland (at a lesser extent), and other urban uses exert significant water demands on wetlands located in urban environments. Of three test scenarios, the one presenting wetlands as water reservoirs seemed promising than those considered optimal (based on policies regulating water use) and rational (stationary inputs but with a decrease in daily allocation). These findings highlight the impact of climate change in the Ruzizi plain, emphasizing the urgency of implementing adaptive measures. This study advocates for the necessity of the IWRM approach to enhance water resilience, fostering sustainable development and wetland preservation under changing climate.

Microplastics promote the invasiveness of invasive alien species under fluctuating water regime

Abstract Microplastic (MP) pollution and alien plant invasions are two important threats to terrestrial ecosystems. Microplastics alter the physical and chemical characteristics of soil, potentially affecting the performance of alien plants. However, previous studies have overlooked the impact of weather on invasive plants in areas polluted by MPs. With the global increase in extreme rainfall events, it is imperative to redefine the correlation between MPs and invasive plants. Here, we conducted an experiment in a climate chamber to examine the effects of MPs on the growth and development of both native and invasive alien plants under constant and fluctuating water regime (FWR). The FWR simulated extreme water pulses during the 2016–2020 growing seasons in Wuhan, China. Our results indicated that biomass accumulation and root development were influenced by water conditions and MP pollution in both invasive and native species. The extent of the effects varied between the two groups of plant species. FWR promoted plant growth and fine root development in invasive plants but reduced the maximum quantum efficiency of photosystem II (Fv/Fm) and nonphotochemical quenching (NPQ) indices of native plants. Moreover, FWR attenuated the negative effects of polybutylene succinate (PBS, degradable MPs) on biomass and root characteristics (length, surface area and tips). FWR compensated the negative impacts of MPs on the total and below‐ground biomass of the invasive species Paspalum dilatatum and Sphagneticola trilobata, but not on the native species. Consequently, invasive species showed better performance than native species in the fine root development of biomass growth and chlorophyll fluorescence under the combined effects of MPs and FWR. Synthesis and applications. Our findings suggest that MP pollution enhances the competitiveness of invasive alien species over the native species when exposed to pronounced dry–wet water cycle conditions, potentially affecting the composition and biodiversity of the ecosystems. Thus, controlling MP pollution should be a part of the management strategy to conserve biodiversity and ecosystems.

Effects of extreme rainfall events on phytoplankton community in a subtropical eutrophic lake: a mesocosm experiment

The impact of global climate change has led to an increase in extreme rainfall events, causing fluctuations in terrigenic inputs that significantly affect aquatic communities. Lake Changhu, the third-largest freshwater lake in Hubei Province, plays a crucial role as a reservoir of aquatic germplasm resources in the middle reaches of the Yangtze River. In recent years, the lake has experienced a series of extreme rainfall events. In response to recent extreme rainfall events, a 42-day mesocosm experiment was conducted to understand the effect of terrigenic inputs on various aspects of phytoplankton in Lake Changhu, such as species composition, abundance, biomass, diversity, community turnover rates, resource use efficiency, and stability. The experiment involved the application of different terrigenic treatments, including a control group (CK, using lake water), low terrigenic input (LT), medium terrigenic input (MT), and high terrigenic input (HT). The results showed a noticeable shift in phytoplankton composition from a co-dominated state of Chlorophyta and Cyanobacteria in the CK treatment to a Cyanobacteria-dominated state in the other terrigenic treatments. Furthermore, the terrigenic inputs increased phytoplankton abundance, community turnover rates, diversity, and resistance. Comparatively, the diversity index of phytoplankton increased by 82.61%, 73.83%, and 70.41% in the LT, MT, and HT treatments, respectively, in contrast to the CK treatment. However, phytoplankton abundance decreased by 6.99%, 15.55%, and 14.76% in the LT, MT, and HT treatments. Additionally, the resource use efficiency decreased by 1.94%, 5.16%, and 14.19% in the LT, MT, and HT treatments, respectively, compared to the CK treatment. These findings provide valuable insights into monitoring and managing the water ecology in Lake Changhu, offering a scientific basis for implementing effective management strategies.

Investigation of the Variability of Dry / Wet Meteorological conditions using the SPEI / SPI Index in the Selo Watershed, Period 1981-2020.

The significant impact of climate change is high variability in rainfall and an increase in extreme rainfall events. The impacts resulted in severe dry/wet conditions. Severe dry conditions can lead to crop failure due to lack of water availability, while severe wet conditions can indicate flooding. This paper aims to investigate the variability of dry/wet meteorological conditions in the Selo watershed. The investigation was carried out using the SPEI and SPI. The results show that wet/dry conditions do not have a clear pattern variability in the long term. Seasonal wet/dry conditions show a changing trend towards wetter conditions in all seasons. Spatially, the changes occur throughout the study area, with the most significant changes occurring in the upstream and downstream parts of the watershed. In the last two decades, wet conditions are more dominant to replace dry conditions that were more prominent in the previous two decades. Other analysis results conclude that there is no influence of air temperature in creating wet/dry conditions in the Selo watershed area. So that the characteristics of wet/dry conditions are very useful for considering the selection of agricultural adaptation strategies in dealing with variability and climate change in the Selo watershed area.

Analysis of Historical and Future Rainfall Projections in India's Lower Godavari Basin

Changes in evaporation and precipitation in the climate are precursors to changes in the water cycle due to the increase in temperatures due to climate change. In recent years, enormous changes in precipitation patterns have led to an increase in extreme rainfall events, reflecting flash floods in smaller areas. To understand this, you must study the rainfall patterns of the district and the smaller watersheds. In the present study, we have observed the trend of rainfall in the lower Godavari basin, which was part of the Godavari River from 1970 to 2019, using IMD 0.25X0.25 ° gridded rainfall data. According to the study, during the winter season and before the monsoon, there is no significant increasing or decreasing trend. In the post-monsoon season they are showing a negative and decreasing trend with a magnitude of 4 mm/year. But in the monsoon season, one end (the right end near the river mouth) of the basin or watershed is showing an increasing trend, while the left part is showing a significantly decreasing trend. In addition to that, future projections of the CMIP5 two scenarios data from 2000 to 2100 to understand the precipitation patterns in future projections. Lower Godavari basin from 2020–2040 and 2040-2100 with the RCP 4.5 and RCP 8.5 scenarios. With the RCP 4.5 scenario, the first 40 years (2020–2040) of the future projected mean seasonal rainfall are 4.5 mm/year higher in the western part of the sub-basin than in the eastern and river mouth regions.

Appraisal of Daily Temperature and Rainfall Events in the Context of Global Warming in South Australia

In recent decades, there have been significant problems worldwide related to global warming and the intensification of extreme temperature and rainfall events. This research evaluated daily temperature and rainfall indices trends to identify whether warming signals have occurred in South Australia over the past fifty years. Extreme cold, hot, and rainfall events were calculated using climatic data from 37 weather stations. A Mann–Kendall test was used for trend analysis with Sen’s estimator. As a result, we determined that for the 1970–2021 period, the maximum and minimum temperatures increased by 1.1 and 0.7 °C, respectively, while precipitation had a negative trend (−52.2 mm per period). Since statistical significance was found in analysing extreme cold and hot events, we find that warming signals have several impacts on South Australia. In the case of rainfall events, we identified a heterogeneous pattern characterised by a reduction in the annual amount and an increase in extreme rainfall events. The findings enable us to conclude that the area shows signs of global warming that could affect the intensity and magnitude of droughts. This information is essential for continuing with current management strategies to adapt and mitigate the effects of global warming in South Australia.

Data driven real-time prediction of urban floods with spatial and temporal distribution

The increase in extreme rainfall events due to climate change, combined with urbanisation, leads to increased risks to urban infrastructure and human life. Physically based urban flood models capable of producing water depth maps with sufficient spatial and temporal resolution are generally too slow for decision makers to react in time during an extreme event. We present a surrogate model with high temporal and spatial resolution for real-time prediction of water levels during a pluvial urban flood. We used machine learning techniques to achieve short computation times. The recursive approach used in this work combines convolutional and fully coupled multilayer architectures. The database for the machine learning was pre-simulated results from a physically based urban flood model. The forcing input of the prediction is precipitation and the output is water level maps with a temporal resolution of 5 min and a spatial resolution of 6 x 6 meters. The prediction performance can be considered promising for testing the model in real operational applications.

Risk Assessment and Prevention Planning for Collapse Geological Hazards Considering Extreme Rainfall—A Case Study of Laoshan District in Eastern China

Geological disasters refer to adverse geological phenomena that occur under the influence of natural or human factors and cause damage to human life and property. Establishing prevention and control zones based on geological disaster risk assessment results in land planning and management is crucial for ensuring safe regional development. In recent years, there has been an increase in extreme rainfall events, so it is necessary to conduct effective geological hazard and risk assessments for different extreme rainfall conditions. Based on the first national geological disaster risk survey results, this paper uses the analytic hierarchy process (AHP) combined with the information method (IM) to construct four extreme rainfall conditions, namely, 10-year, 20-year, 50-year, and 100-year return periods. The susceptibility, hazard, vulnerability, and risk of geological disasters in the Laoshan District in eastern China are evaluated, and prevention and control zones are established based on the evaluation results. The results show that: (1) There are 121 collapse geological disasters in Laoshan District, generally at a low susceptibility level. (2) A positive correlation exists between extreme rainfall and hazards/risks. With the rainfall condition changing from a 10-year return period to a 100-year return period, the proportion of high-hazard zones increased from 20% to 41%, and high-risk zones increased from 31% to 51%, respectively. The Receiver operating characteristic (ROC) proved that the assessment accuracy was acceptable. (3) Key, sub-key, and general prevention zones have been established, and corresponding prevention and control suggestions have been proposed, providing a reference for geological disaster prevention and early warning in other regions.

Assessing Rainfall Variability in Jamaica Using CHIRPS: Techniques and Measures for Persistence, Long and Short-Term Trends

Jamaica, as a Small Island Developing State (SIDS), is highly vulnerable to weather extremes. As precipitation persistence is a critical factor in determining the susceptibility of an area to risks, this work assesses the spatial and temporal variations of rainfall persistence in Jamaica from 1981 to 2020, using satellite-based information. The Hurst exponent (H) and the serial correlation coefficient (SCC) are used to evaluate the long-term persistence of precipitation and the Persistence Threshold (PT) concept is introduced to provide a description of rainfall characteristics over short periods, specifically, the number of consecutive days with precipitation above or below a set threshold value. The PT method is a novel concept that expands upon the Consecutive Dry Days (CDD) and Consecutive Wet Days (CWD) methods that only consider a threshold of 1 mm. Results show notable temporal and spatial variations in persistence over the decades, with an overall increasing trend in high precipitation persistence and a decreasing trend in low precipitation persistence. Geographically, the northern mountainous area of Jamaica received the most persistent rainfall over the study period with an observed increase in extreme rainfall events. The excess rainfall of the 2001–2010 decade is remarkable in this study, coinciding with the global unprecedented climate extremes during this time. We conclude that the data used in this study is viable for understanding and modeling rainfall trends in SIDS like Jamaica, and the derived PT method is a useful tool for short-term rainfall trends, but it is just one step toward determining flood or drought risk. Further research will focus on developing drought and flood indices.

Application of 210Pbex in elucidating contemporary sedimentary dynamics in the water-level fluctuation zone of the Three Gorges Reservoir, China

Excess 210Pb (210Pbex) has been widely applied as a proxy indicator for establishing the chronology of sediments in lakes where the sedimentation processes comply with the assumptions for using 210Pbex dating models. However, little is known regarding the applicability of 210Pbex to elucidate contemporary seasonal sedimentary dynamics in reservoir water-level fluctuation zones (WLFZs). In the present study, sedimentary core and bulk sediments were collected from the WLFZ of the Three Gorges Reservoir (TGR) in China, and the physical and chemical properties were determined. Results for 210Pbex activity, total organic carbon, and total nitrogen of bulk sediments indicate pronounced elevation-dependent spatial variation (p < 0.05), but 137Cs activity and particle composition show no systematic trends, allowing 210Pbex activity to be used to differentiate seasonal stratigraphy. For the sedimentary core, therefore, sediment layers with lower 210Pbex activity were inferred to represent sedimentation during wet seasons, when the 210Pbex concentration was diluted by a higher suspended sediment load, whereas sediment layers characterised by higher 210Pbex activity were ascribed to sedimentation during dry seasons, when the tranquil water favoured 210Pbex fallout to be absorbed by suspended sediments and then deposited in the WLFZ. Hereupon, temporal variation is observed in annual sedimentary thickness, with relatively low sedimentation rates during the initial stage (2006–2008) of the TGR impoundment, followed by relatively high sedimentation rates from 2009 to 2013. Over the period from 2014 to 2017, sedimentation rates were low because the suspended sediment was intercepted by upstream cascade reservoirs. Subsequently, sedimentation rates were higher during 2018–2019 as a consequence of an increase in extreme rainfall events. The findings herein highlight that 210Pbex-based seasonal stratification discrimination is effective approach to establish high-resolution sedimentary chronosequences and that net sedimentation rates in WLFZ are controlled by inflow suspended load of the TGR.

Perceptions of Climate Change Risk on Agriculture Livelihood in Savanna Region, Northern Togo

The agriculture sector in the Savanna region of Togo is especially vulnerable to weather fluctuations, which have an impact on crop production levels. However, farmers’ decisions to implement adaptation strategies are directly related to their perceptions of climate change risk. The current study employed a participatory workshop and household survey of 425 farmers to examine the drivers of specific climate change risks of interest (risk of loss of livelihood for farmers) and measure farmers’ level of climate change risk perception. A climate change risk perception score (CCRPS), descriptive statistics, principal component analysis, and K-means cluster analysis were used to analyze the data collected. The findings revealed that the most important changes in climate conditions affecting agricultural production in the study area were mainly the increased duration of dry spells, erratic rainfall, and an increase in extreme rainfall events. These climatic variations cause more floods and droughts, which, when coupled with socio-ecological vulnerability drivers, increase the impact of these events on agricultural livelihood, expose more farmers and their farmland, and contribute to the risk of farmers’ livelihood loss in the study area. Based on farmers’ appraisals of the occurrence of hazards, their exposure, and their vulnerability, farmers’ perceptions of climate risk have been classified into three categories: high, moderate, and low. This finding sheds some light on farmers’ climate change risk perception, which may influence their adaptation decision. These findings can be used to increase the uptake of adaptation strategies and thus the resilience of Savanna region agriculture to climate change.

Rainfall Wet Spells Variability Across Temperature Mean‐Change Years in the Northwestern Himalayan Region

AbstractTemperatures have risen at a faster rate across various mountainous regions around the world. A study of the changing rainfall patterns and their spatiotemporal variability is critical for agricultural, water resource, and hydrological planning and management. The goal of this research is twofold: first, using functional data analysis climate change hotspots are determined, which in turn identified most temperature increases in high elevations. Second, these hotspots are utilized to investigate the impact of temperature changes on the frequency of extreme rainfall events in this Northwestern Himalaya region. Our study observed that the frequency of rainfall extremes, such as, at the 90th, 95th, and 99.99th percentile values, is found to be increasing mostly in lower Himalayan regions. A warmer atmosphere leads to heavy precipitation events as the capacity of air to hold moisture increases with the increase in temperature. The continuous temperature rise possibly indicates an increase in extreme rainfall events in the region. Further, this study reports an interesting finding that can help us better understand the impact of climate change in the region: the frequency of shorter wet spells has increased around the recent mean‐change year, whereas the frequency of long spells has reduced. The frequency of longest wet spells shows a decrease across all seasons, leading to drought in the higher altitude region, whereas the short‐wet spell frequency has increased in the lower altitude regions. Insight into the changing patterns of rainfall is crucial for hydrological and agricultural management.

Assessing the impact of climate change on Combined Sewer Overflows based on small time step future rainfall timeseries and long-term continuous sewer network modelling

The evolution of the climate in the future will probably lead to an increase in extreme rainfall events, particularly in the Mediterranean regions. This change in rainfall patterns will have impacts on combined sewer systems operation with a possible increase of spilled flows, leading to an increase of untreated water volumes released to the receiving water. Due to the impact of overflows on the water cycle, local authorities managing combined sewer systems are wondering about the extent of these changes and the possibility of taking it into account in stormwater management structure design. To do this, rainfall data with a fine time step are required to better master the shape of the hyetographs that are crucial to get a relevant rainfall/runoff relationship in an urban environment. However, there are currently no simulations of future rainfall series available at a time step compatible with the needs in urban drainage field. In this work, future rainfall time series with a fine time step are elaborated with the aim to be used in urban hydrology. The proposed approach is based on simulations results from five regional climate models in the framework of the Euro-Cordex program. It consists in a spatial downscaling step followed by a temporal disaggregation. The rainfall time series obtained are then used as input for a calibrated and validated hydrological model to investigate the evolution of annual CSO volumes and frequencies by 2100. The results show an increase of annual spilled volumes between 13% and 52% according to the considered climate model. This increase will most likely be a problem regarding compliance of sewer networks in line with the water framework directive, particularly the current French regulations. No clear trends were observed on the CSO frequencies. If there is a consensus for all the carried-out simulations to conclude that the CSO volumes will increase, we must remember that actual regional climate models suffer from limited spatial and temporal resolution and don't explicitly solve convection processes. Due to this point uncertainty concerning the evolution rate remains important particularly for intense rainfall episodes. New generations of climate models are needed to accurately predict intense episodes.

Probabilistic modeling of sustainable urban drainage systems

Sustainable Urban Drainage Systems (SUDS) include strategies and solutions for distributed stormwater management and control. They are strongly encouraged, especially in highly urbanized areas that suffer the combined effect of impervious surfaces and the increase in extreme rainfall events due to urbanization growth and climate change. Their integration into traditional urban drainage systems can mitigate flood risk and pollution of receiving water bodies. The main goal of SUDS is to restore the natural water balance by increasing infiltration and evapotranspiration processes and promoting rainwater harvesting and reuse. This paper proposes an analytical-probabilistic approach for SUDS modeling applicable to different systems. Developed equations allow estimating the runoff and residual storage probability for evaluating the efficiency of the storage volume both in terms of flood control and, depending on SUDS type, in terms of emptying time or water needs supply. The modeling considers the possibility of consecutive chained rainfalls; this feature is relevant for SUDS, often characterized by low outflow rates. Relating characteristic parameters to a probabilistic level (the Average Return Interval, ARI) makes the formulas interesting to be used in the design practice. An application to two case studies confirmed the goodness of the proposed method.

Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review

A flash flood disaster is one of the most destructive natural disasters. With the increase in extreme rainfall events, more and more areas will be threatened by flash floods. The flash flood susceptibility assessment is the basis of flash flood risk assessment and is also an important step in flash flood disaster management. Based on Citespace analysis tools, this study made a bibliometric and visualized analysis of 305 documents collected in the core collection of Web of Science in the past 15 years, including the analysis of the number of publications and citation frequency, influence analysis, keyword analysis, author co-citation analysis, and institutional co-operation analysis. This paper summarizes the current research status and future development trend of flash flood susceptibility assessment from five key research subfields, including assessment scale, assessment unit, assessment index, assessment model, and model assessment method, discusses the analysis of the application of remote sensing and GIS in flash flood susceptibility assessment, discusses the problems encountered in the current research of the five subfields, and provides suggestions for flash flood hazard control.

Potential Use of Extreme Rainfall Forecast and Socio-Economic Data for Impact-Based Forecasting at the District Level in Northern India

Due to the increase in extreme rainfall events in India, there is an urgent need for prior communication of the expected impacts and appropriate responses in order to mitigate the losses of lives and damage to property. Extreme rainfall events cause numerous casualties, damage to property and infrastructure and vast displacement of people. Hence, the development of an approach where the rainfall forecasts are well analyzed, associated risks are identified, and the probable impacts are clearly communicated to relevant stakeholders is required. In this study, we aim to develop a framework for generating the impact-based forecasts (IBF) and associated warning matrices over the selected districts of eastern Uttar Pradesh, India, by integrating the rainfall forecasts and the socio-economic characteristics such as population, economy and agriculture. The selected districts lack proper infrastructure, have poor socio-economic conditions and have been historically prone to frequent extreme rainfall. The basic idea is to estimate the impacts that could occur over various sectors of population, economy and agriculture and suggest appropriate actions in order to mitigate the severity of the impacts. To this end, we identify the vulnerable districts based on the frequency of the number of extreme rainfall forecasts (ERFs) in the past four years (2017–2020) and the nature of socio-economic conditions. We selected three vulnerable districts based on the expected impacts, i.e., Shravasti (high category), Gorakhpur (medium category) and Jaunpur (low category) and subsequently, the corresponding IBFs are generated. Furthermore, a warning matrix is created for each district which provides updated information regarding the potential risk for a district a few days in advance. This study is significant since it identifies the different levels of potential impact over multiple sectors of society, presents a framework to generate impact-based forecasts and warnings, informs about the expected impacts, and suggests mitigation actions to reduce potential damage and losses.

Storm and floods increase the duration and extent of phosphorus limitation on algal blooms in a tributary of the Three Gorges Reservoir, China

Excessive anthropogenic nutrient input has resulted in eutrophication and algal blooms which have severely impacted the function and sustainability of aquatic ecosystems, underscoring the need to implement nutrient management strategies. It was assumed that the increasing rainfall during flood season would affect the stoichiometric ratio of total nitrogen (TN): total phosphorus (TP), driving the nutrient limitation of algal growth. In order to test this concept and explore corresponding nutrient management strategies, nutrient addition bioassays were carried out in Xiangxi Bay, one of the largest tributaries of the Three Gorges Reservoir (TGR), China. Results indicated that nutrient limitation on algal growth fluctuated from nitrogen (N) to phosphorus (P) limitation. N limitation dominated in the early flood season. However, the reduction of dissolved P, accompanied with an increase of TN: TP caused by an increase in extreme rainfall events intensified P limitation throughout the bay. Then P limitation was alleviated due to the reduction of rainfall and the process of impoundment after the flood season. The variation of TN: TP caused by the increasing of rainfall and flooding could be the main driving factor of the nutrient limitation shift in aquatic ecosystems mainly affected by external nutrient inputs. Nutrient dilution and enrichment bioassays showed that TN and TP concentration thresholds should be targeted at below 0.55 mg/L and 0.057 ∼ 0.064 mg/L respectively, to limit the growth of algae and maintain chlorophyll a below 30 μg/L. Dual nutrient (N & P) reductions were required for long-term bloom mitigation in the entire basin. This study provided a scientific basis for a nutrient management strategy to combat eutrophication and reduce algal bloom potentials in the tributaries of the TGR. We recommend that long-term determinations of nutrient limitation and nutrient threshold will be needed to control algal growth, considering future anticipated changes in land use, population density and the impacts of climate change.

Evaluating the contribution of different environmental drivers to changes in evapotranspiration and soil moisture, a case study of the Wudaogou Experimental Station

Evapotranspiration and soil moisture content (SMC) are key elements of the hydrological cycle. Accurate prediction of the dynamic processes of evapotranspiration and soil water is essential for irrigation and water management. Here, the boosted regression tree (BRT) method was employed to quantify environmental controls on actual evapotranspiration (ETa), potential evapotranspiration (ET0), and SMC using monitoring data from the Wudaogou hydrological experimental station. The results indicated that: (1) the BRT algorithm was effective in predicting the relative control of different environmental factors on ETa, ET0, and SMC; and (2) vapor pressure deficit (VPD) was the most important factor affecting daily ET0, and sunshine duration (SSD) also played a nonnegligible role. The results further explained the phenomenon of the “evaporation paradox” in the study area. SSD could be a leading control on daily ETa, followed by VPD, leaf area index (LAI). (3) Among the underground factors, groundwater level (GL) and LAI played a dominant role in the relative contribution to SMC. Among the aboveground factors, relative humidity (RH) and soil temperature (TS) have a relatively large influence on SMC. (4) The differences in SMC at different depths were determined by multiple influencing factors, including LAI, VPD, and precipitation (P). This study also underscores the importance of vegetation variations to hydrological cycle processes. In general, climate warming and an increase in extreme rainfall events will increase the control of temperature on SMC and weaken the control of P on SMC in the future.