Flood inundation assessment for the Hanoi Central Area, Vietnam under historical and extreme rainfall conditions

Impact of climate change on human health: evidence from riverine island dwellers of Bangladesh

This study aims to explore the impact of climate change on health, including local adaptation strategies. A mixed-method approach has been used in this study. The results reveal that increasing the frequency of flooding, severity of riverbank erosion and drought, and rising disease outbreak are the highest indicators of climate change perceived by riverine island (char) dwellers, which is similar to the observed data. It also uncovers, approximately all respondents encounter several health-related issues during different seasons where prevailing cold and cough with fever, skin diseases, and diarrhoea are the leading ailments. Several adaptation strategies are accommodated by char inhabitants in order to enhance resilience against the climate change health impacts, but the paucity of money, disrupted communication, lack of formal health-care centre are the most obstacles to the sustainability of adaptation. This research recommends that healthcare-associated project should be performed through proper monitoring for exterminating char dwellers' health issues.

Landscape pattern change and its correlation with influencing factors in semiarid areas, northwestern China

The West Liaohe Plain (WLP) is a typical crop-pastoral ecotone of the semiarid area in Northwestern, China. Land use/cover change (LUCC) of the WLP might endanger this ecosystem, triggering long-lasting environmental concerns. LUCC data for China (1980-2020) and hydrometeorological data were analyzed to reveal factors contributing to change and explore sustainable development opportunities. The results show that characteristics of the main land-use types in the WLP have changed significantly, especially cultivated land area, which increased by 15.2% and 6.79% during the periods 1980-1995 and 2000-2020, respectively. Response relationships were observed due to natural (precipitation, temperature, and runoff) and anthropogenic (economy) factors and LUCC. Between 2000 and 2020, the impact of anthropogenic factors on cultivated land was stronger than on grassland at the class and landscape level, using the landscape indices which were selected, including percent of landscape (PLAND), number of patches (NP), largest patch index (LPI), and Shannon's evenness index (SHEI). Expansion of cultivated land from 1990 to 1995 was not only related to anthropogenic factors but also to hydrological & climatic factors. The results of this study have the potential to influence sustainable land resource development.

Community Scale Assessment of the Effectiveness of Designed Discharge Routes from Building Roofs for Stormwater Reduction

Urban flooding is increasing due to climate change and the expansion of impervious land surfaces. Green roofs have recently been identified as effective solutions for mitigating urban stormwater. However, discharge routes that involve receiving catchments of stormwater runoff from roofs to mitigate high flows have been limited. Thus, a hydrological model was constructed to investigate the effects of changing discharge routes on stormwater flow. Three hypothetical scenarios were assessed using various combinations of discharge routes and roof types. The reduction effects on outflow and overflow were identified and evaluated across six return periods of designed rainstorms in the Tai Hung Tulip House community in Beijing. The results showed that green roofs, together with the discharge routes connecting to pervious catchments, were effective in reducing peak flow (13.9–17.3%), outflow volume (16.3–27.3%), drainage overflow frequency, and flood duration. Although mitigation can be improved by considering discharge routes, it is limited compared to that achieved by the effects of green roofs. However, integrating green roofs and discharge routes can improve community resilience to rainstorms with longer return periods. These results provide useful information for effective design of future stormwater mitigation and management strategies in small-scale urban areas.

Impact of Mountain Reservoir Construction on Groundwater Level in Downstream Loess Areas in Guanzhong Basin, China

An accurate understanding of the relationship between reservoir construction and the dynamic change of groundwater level in downstream areas is of great significance for rational development and utilization of water resources. At present, the research on the interaction between surface water (SW) and groundwater (GW) mainly focuses on the interaction between river and GW. There are few studies on the impact of the reservoir construction on GW level in downstream loess irrigation area. Rainfall, evaporation and climate temperature have a great impact on W level, but the impact of reservoir construction on the GW level should not be ignored in the utilization of water resources. In this paper, a GW flow model under a natural boundary was established by numerical simulation. Taking Heihe Jinpen Reservoir in Heihe River watershed as the research object, the influence of the construction of a mountain reservoir on the dynamic change of GW level in the downstream loess region is studied. By comparing the GW level under the natural state without reservoir construction and the measured GW level after the reservoir was built, the variation of the GW depth in the loess area of the lower reaches in the Heihe River watershed is obtained. The results show that simulation accuracy of the interaction between SW and GW was reasonable; after the Heihe Jinpen Reservoir construction, the mean GW level decrease was about 6.05 m in the downstream loess irrigation area in Guanzhong Basin. It provides a method for the simulation and prediction of SW–GW conversion laws. This study is also of great significance to explore the change law of the water cycle and improve the utilization rate of water resources.

Exploring sustainable solutions for the water environment in Chinese and Southeast Asian cities

Water is essential for human activities and economic development, and the water environment significantly influences ecological balance and global climate. China and Southeast Asia are the most populous areas in the world, and their water resources are deteriorating day by day. We focus on five representative cities such as, Beijing, Jakarta, Hanoi, Kathmandu and Manila to investigate water-environmental problems with the ultimate goal of providing recommendations for sustainable urban water management. The study found that (1) the water environment of all cities has been polluted to varying levels, while the pollution has improved in Beijing and Jakarta, and the situation in other regions is severe. (2) The aquatic biodiversity has reduced, and its pollution is mainly caused by organic pollutants and decreasing river flow. In addition, numerous people live in megacities without access to clean surface water or piped drinking water, which greatly increases the use of groundwater. Further, frequent floods in the world leads to serious damage to urban infrastructure and further deterioration of water environment quality. To address these problems, countries and organizations have begun to construct wastewater treatment plants and develop water-saving technology to ensure healthy and sustainable development of water environment. The results and practical recommendations of this study can provide scientific insights for future research and management strategies to address water quality challenges during ongoing policy debates and decision-making processes.

Impact of China’s Provincial Government Debt on Economic Growth and Sustainable Development

Macroeconomic stability is the core concept of sustainable development. However, the coronavirus disease (COVID-19) pandemic has caused government debt problems worldwide. In this context, it is of practical significance to study the impact of government debt on economic growth and fluctuations. Based on panel data of 30 provinces in China from 2012 to 2019, we used the Mann–Kendall method and Kernel Density estimation to analyze the temporal and spatial evolution of China’s provincial government debt ratio and adopted a panel model and HP filtering method to study the impact of provincial government debt on economic growth and fluctuation. Our findings indicate that, during the sample period, China’s provincial government debt promoted economic growth and the regression coefficient (0.024) was significant. From different regional perspectives, the promotion effect of the central region (0.027) is higher than that of the eastern (0.020) and western regions (0.023). There is a nonlinear relationship between China’s provincial government debt and economic growth, showing an inverted “U-shaped” curve. Fluctuations in government debt aggravate economic volatility, with a coefficient of 0.009; tax burden fluctuation and population growth rate aggravate economic changes. In contrast, the optimization of the province’s industrial structure and the improvement of the opening level of provinces slow down economic fluctuations.

Quantifying the Contributions of Climate Change and Human Activities to Water Volume in Lake Qinghai, China

Lake Qinghai has shrunk and then expanded over the past few decades. Quantifying the contributions of climate change and human activities to lake variation is important for water resource management and adaptation to climate change. In this study, we calculated the water volume change of Lake Qinghai, analyzed the climate and land use changes in Lake Qinghai catchment, and distinguished the contributions of climate change and local human activities to water volume change. The results showed that lake water volume decreased by 9.48 km3 from 1975 to 2004 and increased by 15.18 km3 from 2005 to 2020. The climate in Lake Qinghai catchment is becoming warmer and more pluvial, and the changes in land use have been minimal. Based on the Soil and Water Assessment Tool (SWAT), land use change, climate change and interaction effect of them contributed to 7.46%, 93.13% and −0.59%, respectively, on the variation in surface runoff into the lake. From the perspective of the water balance, we calculated the proportion of each component flowing into and out of the lake and found that the contribution of climate change to lake water volume change was 97.55%, while the local human activities contribution was only 2.45%. Thus, climate change had the dominant impact on water volume change in Lake Qinghai.

Case Study of Urban Flood Inundation—Impact of Temporal Variability in Rainfall Events

This study aimed to calculate and analyze total overflows that accumulate in urban manholes in the target drainage basin of Samsung-dong, Seoul in heavy rainfall events with different temporal distribution characteristics, using the EPA’s Storm Water Management Model (EPA-SWMM model). Inundation behaviors were analyzed using the two-dimensional flood model (FLO-2D). The extreme rainfall events were produced using different exceedance probability Huff distributions for different durations and return periods, such as from 1 to 3 h and 10 years, 50 years, 80 years, 100 years, respectively. The inundation model was validated using the actual flood observations on 21 September 2010 in the Samsung-dong drainage basin. The total overflow amount showed considerable differences according to the different time distribution characteristics, such as the temporal location of the storm peak and the concentration level of the storm. Furthermore, the inundation behaviors were also related to the temporal characteristics of storms. The results illustrated that the consideration of the temporal distribution characteristics of extreme rainfall events is essential for an accurate understanding of the rainfall–runoff response and inundation behavior in urban drainage basins.

Retrieving zinc concentrations in topsoil with reflectance spectroscopy at Opencast Coal Mine sites

Heavy metals contaminations in mining areas aroused wide concerns globally. Efficient evaluation of its pollution status is a basis for further soil reclamation. Visible and near-infrared reflectance (Vis-NIR) spectroscopy has been diffusely used for retrieving heavy metals concentrations. However, the reliability and feasibility of calibrated models were still doubtful. The present study estimated zinc (Zn) concentrations via the random forest (RF) and partial least squares regression (PLSR) using ground in-situ Zn concentrations as well as soil spectral reflectance at an Opencast Coal Mine of Ordos, China in February 2020. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and the ratio of performance to deviation (RPD) were selected to assess the robustness of the methods in estimating Zn contents. Moreover, the characteristic bands were chosen by Pearson correlation analysis and Boruta Algorithm. Finally, the comparison between RF and PLSR combined with eight spectral reflectance transformation methods was conducted for four concentration groups to determine the optimal model. The results indicated that: (1) Zn contents represented a skewed distribution (coefficient of variation (CV) = 33%); (2) the spectral reflectance tended to decrease with the increase of Zn contents during 580-1850 nm based on Savitzky-Golay smoothing (SG); (3) the continuous wavelet transform (CWT) demonstrated higher effectiveness than other spectral reflectance transformation methods in enhancing spectral responses, the R2 between Zn contents and the soil spectral reflectance achieved the highest (R2 = 0.71) by using CWT; (4) the RF combined with CWT exhibited the best performance than other methods in the current study (R2 = 0.97, RPD = 3.39, RMSE = 1.05 mg kg-1, MAE = 0.79 mg kg-1). The current study supplied a scientific scheme and theoretical support for predicting heavy metals concentrations via the Vis-NIR spectral method in possible contaminated areas such as coal mines and metallic mineral deposit areas.

Dynamic Assessment of the Impact of Flood Disaster on Economy and Population under Extreme Rainstorm Events

In the context of climate change and rapid urbanization, flood disaster loss caused by extreme rainstorm events is becoming more and more serious. An accurate assessment of flood disaster loss has become a key issue. In this study, extreme rainstorm scenarios with 50- and 100-year return periods based on the Chicago rain pattern were designed. The dynamic change process of flood disaster loss was obtained by using a 1D–2D coupled model, Hazard Rating (HR) method, machine learning, and ArcPy script. The results show that under extreme rainstorm events, the direct economic loss and affected population account for about 3% of the total GDP and 16% of the total population, respectively, and built-up land is the main disaster area. In addition, the initial time and the peak time of flood disaster loss increases with an increasing flood hazard degree and decreases with the increase in the return period. The total loss increases with the increase in the return period, and the unit loss decreases with the increase in the return period. Compared with a static assessment, a dynamic assessment can better reveal the development law of flood disaster loss, which has great significance for flood risk management and the mitigation of flood disaster loss.

Cloud Transform Algorithm Based Model for Hydrological Variable Frequency Analysis

Hydrological variable frequency analysis is a fundamental task for water resource management and water conservancy project design. Given the deficiencies of higher distribution features for the upper tail section of hydrological variable frequency curves and the corresponding safer resulting design of water conservancy projects utilizing the empirical frequency formula and Pearson type III function-based curve fitting method, the normal cloud transform algorithm-based model for hydrological variable frequency analysis was proposed through estimation of the sample empirical frequency by the normal cloud transform algorithm, and determining the cumulative probability distribution curve by overlapping calculation of multiple conceptual cloud distribution patterns, which is also the primary innovation of the paper. Its application result in northern Anhui province, China indicated that the varying trend of the cumulative probability distribution curve of annual precipitation derived from the proposed approach was basically consistent with the result obtained through the traditional empirical frequency formula. Furthermore, the upper tail section of the annual precipitation frequency curve derived from the cloud transform algorithm varied below the calculation result utilizing the traditional empirical frequency formula, which indicated that the annual precipitation frequency calculation result utilizing the cloud transform algorithm was more optimal compared to the results obtained by the traditional empirical frequency formula. Therefore, the proposed cloud transform algorithm-based model was reliable and effective for hydrological variable frequency analysis, which can be further applied in the related research field of hydrological process analysis.

Evaluation on the Change Characteristics of Ecosystem Service Function in the Northern Xinjiang Based on Land Use Change

Monitoring the interannual changes in land use and the temporal and spatial characteristics of the ecosystem services value (ESV) can help to comprehensively and objectively understand the distribution of regional ecological patterns. The mountain–oasis–desert transition zone in the northern Tianshan Mountain region of Xinjiang, China, is a geographically unique area with a highly sensitive ecosystem. As a data source, the study uses Landsat TM images from 1990, 2000, 2010, and 2018 along with GIS-extracted data to calculate the dynamic degree of land use. As well, the spatial and temporal patterns of land use change and ESV are quantitatively analyzed by using the equivalent factor method, sensitivity index, and spatial correlation studies. The results reveal the following: (1) From 1990 to 2018, the land use changes in the northern Tianshans are relatively drastic, mainly due to the increase in cultivated land, grassland and construction land, and the decrease in forest land, water, and unused land. (2) The ESV increases and then decreases, for a total loss of about 271.63 × 108 yuan. The largest decrease is in forest value, and the largest increase (around 129.94%) is in construction land. (3) The spatial distribution pattern of ESV in the northern Tianshans is apparent, showing high in the north and southwest, and low in the central and southeast portions of the study area. Additionally, there is a visible spatial correlation and aggregation in ESV. The present research can provide theoretical support for the environmental protection of the ecologically vulnerable area of the northern Tianshans as well as for further construction across the region.

Potential Land Use Conflict Identification Based on Improved Multi-Objective Suitability Evaluation

Accurately identifying potential land use conflicts (LUCs) is critical for alleviating the ever-intensifying contradictions between humans and nature. The previous studies using the method of suitability analysis did not take full advantage of the current land use and multi-function characteristics of land resources. In this study, an improved model of suitability analysis was realized. In order to explore the LUCs status, including the types, intensity and distribution, a multi-objective suitability evaluation model was constructed from the perspective of production-living-ecological functions. And it was applied to Hengkou District, a typical region of the Qin-Ba mountainous area in the central part of China. The results show that the suitability distribution of living- production-ecological functions vary widely from the center to the periphery with altitude in Hengkou District; 22.03% of the land is at a risk of land use conflict. Among them, the high potential conflict areas account for 55.32%, and the conflicts between production and ecological lands (L2P1E1, L3P1E1) are the largest, which are located at the fringe of the central urban and ecologically dominant area. Therefore, it is necessary to adopt effective strategies to achieve a balance between the differential demands of land use. This research could better reflect the true situation of land use in ecologically sensitive mountainous areas and would provide theoretical and methodological support for the identification and prevention of potential LUCs.

Mapping the spatial and temporal variability of flood susceptibility using remotely sensed normalized difference vegetation index and the forecasted changes in the future

Accurate runoff forecasting plays a considerable role in the appropriate water resource planning and management. The spatial and temporal evaluation of the flood susceptibility was explored in the Quebec basin, Canada. This study provides a new strategy for runoff modelling as one of the complicated variables by developing new machine learning techniques along with remote sensing. A novel scheme of the Group Method of Data Handling (GMDH) known as the generalized structure of GMDH (GSGGMDH) is developed to overcome this classical approach's limitation. A simple time series based scenario with exogenous variables including precipitation and Normalized Difference Vegetation Index (NDVI) was introduced for runoff forecasting. MODIS data included MOD13Q1 product was employed and a JavaScript code was developed to preprocess collected data in the Google Earth Engine (GEE) environment. Using different seasonal and non-seasonal lags of all input variables, the developed GSGMDH found the most optimum input combination for each station in terms of simplicity and accuracy, simultaneously (average values; SI = 0.554, RMSRE = 1.55, MAE = 5.076). The precipitation values are modelled with the CanEsm2 climate change model. To apply NDVI for runoff forecasting, a simple spatial-temporal GSGMDH based model was developed (average values; SI = 0.27; RMSRE = 8.27, MAE = 0.08). The forecasting results indicated that the months in which the maximum runoff occurred have changed, and these months have increased compared to the historic period. In the historical period, the frequency of maximum runoff was in April and March. Still, for the two forecasting periods (i.e. 2020-2039 and 2040-2059), the months in which the maximum runoff has occurred have changed, and their amount has been reduced and added to other months, especially February and August.

Analysis of the Spatiotemporal Changes in Watershed Landscape Pattern and Its Influencing Factors in Rapidly Urbanizing Areas Using Satellite Data

Analyzing the spatiotemporal characteristics and causes of landscape pattern changes in watersheds around big cities is essential for understanding the ecological consequence of urbanization and provides a basic reference for the watershed management. This study used a land-use transition matrix and landscape indices to explore the spatiotemporal change of land use and landscape pattern over Liuxihe River basin of Guangzhou in the southeast of China from 1980 to 2015 with multitemporal Landsat satellite data in response to the rapid urbanization process. Primary temporal and spatial influencing factors were first quantitatively identified through grey relation analysis (calculating correlation degree between land use changes and influencing factors) and Geodetector (detecting landscape spatial heterogeneity and its driving factors), respectively. Considerable spatial and temporal differences in land use and landscape pattern changes were observed herein, thus determining the influencing factors of these differences in the Liuxihe River basin. These changes were characterized by a large increase in construction land converted from cropland, particularly in the middle and lower reaches of the basin from 2000 to 2010, causing dramatic fragmentation and homogenization of the landscape pattern there. Meanwhile, the landscape pattern gradually transitioned from an agricultural land use dominant landscape to a construction land use dominant landscape in these regions. Furthermore, the rapid growth of a nonagricultural population and the transformation of industry primarily caused the temporal changes of landscape pattern, and the landscape spatial heterogeneity was mainly caused by the interaction of complicated geomorphology and anthropogenic activities in different spatial locations, particularly after 2000. This study not only provides an improved approach to quantifying the main spatiotemporal influencing factors of landscape pattern changes during different time periods, but also offers a reference for decision-makers to formulate optimal strategies on ecological protection and urban sustainable development of different regions in this study area.

Assimilation of Multi-Source Precipitation Data over Southeast China Using a Nonparametric Framework

The accuracy of the rain distribution could be enhanced by assimilating the remotely sensed and gauge-based precipitation data. In this study, a new nonparametric general regression (NGR) framework was proposed to assimilate satellite- and gauge-based rainfall data over southeast China (SEC). The assimilated rainfall data in Meiyu and Typhoon seasons, in different months, as well as during rainfall events with various rainfall intensities were evaluated to assess the performance of this proposed framework. In rainy season (Meiyu and Typhoon seasons), the proposed method obtained the estimates with smaller total absolute deviations than those of the other satellite products (i.e., 3B42RT and 3B42V7). In general, the NGR framework outperformed the original satellites generally on root-mean-square error (RMSE) and mean absolute error (MAE), especially on Nash-Sutcliffe coefficient of efficiency (NSE). At monthly scale, the performance of assimilated data by NGR was better than those of satellite-based products in most months, by exhibiting larger correlation coefficients (CC) in 6 months, smaller RMSE and MAE in at least 9 months and larger NSE in 9 months, respectively. Moreover, the estimates from NGR have been proven to perform better than the two satellite-based products with respect to the simulation of the gauge observations under different rainfall scenarios (i.e., light rain, moderate rain and heavy rain).

Quantifying the inundation impacts of earthquake-induced surface elevation change by hydrological and hydraulic modeling

Current estimates of flood hazards are often based on the assumption that topography is static. When tectonic and/or anthropogenic processes change the land surface elevation, the spatial patterns of floods might also change. Here, we employ the hydrological and hydraulic modeling to simulate floods in the Kujukuri Plain, Japan, in the years 2004 and 2013, when two severe floods occurred. In between the two floods, land surface elevations were changed by the 2011 Tohoku-Oki earthquake. The effects of land surface elevation changes on inundation areas were quantified by changing input topographies. Our results showed that, without taking into account land surface elevation changes, around 10% of inundation areas were underestimated at the time of flood events in the year 2013. The spatial distribution of inundation locations varied with local topographical features, for example, the areas with backmarsh and valley fill deposits were sensitive to the extent of inundation by land surface elevation changes. The sub-watershed near the coastal shoreline having below-zero meter elevation areas showed that the earthquake-induced land surface elevation changes exacerbated an additional 22% inundation area. This study suggests that the inundation areas will increase in catchments suffering severe settlements, which highlights the necessity of taking into account the spatio-temporal changes of land surface elevations on the assessment of flood hazards.

The Relationship between Coordination Degree of the Water–Energy–Food System and Regional Economic Development

The sustainable development of the water–energy–food (WEF) system has gained global attention as a result of limited land resources, inadequate energy supply and growing water stress. Coordination degree is an important indicator to measure the sustainable development of the WEF system. Improving the coordination degree contributes to the sustainable development of the WEF system and affects regional economic development. The extended Cobb–Douglas function is applied to examine the relationship between coordination degree of the WEF system and regional economic development in 31 provinces of China during the period of 2007–2018. By using the system generalized method of moments (GMM) estimation, empirical results indicate that in the regions with low coordination degree, improved coordination degree of the WEF system will hinder regional economic growth. In the regions with high coordination degree, it will promote regional economic growth. The results indicate that there is a lag period for the influence of improved coordination degree on regional economic growth. When making resources management policies, shortening the lag period is conducive to achieving sustainable development and promoting regional economic development. Governments of various regions should formulate different resource management policies based on the conditions of each region and the different relationships between coordination degree of the WEF system and regional economic development.

Research on Runoff Simulations Using Deep-Learning Methods

Runoff simulations are of great significance to the planning management of water resources. Here, we discussed the influence of the model component, model parameters and model input on runoff modeling, taking Hanjiang River Basin as the research area. Convolution kernel and attention mechanism were introduced into an LSTM network, and a new data-driven model Conv-TALSTM was developed. The model parameters were analyzed based on the Conv-TALSTM, and the results suggested that the optimal parameters were greatly affected by the correlation between the input data and output data. We compared the performance of Conv-TALSTM and variant models (TALSTM, Conv-LSTM, LSTM), and found that Conv-TALSTM can reproduce high flow more accurately. Moreover, the results were comparable when the model was trained with meteorological or hydrological variables, whereas the peak values with hydrological data were closer to the observations. When the two datasets were combined, the performance of the model was better. Additionally, Conv-TALSTM was also compared with an ANN (artificial neural network) and Wetspa (a distributed model for Water and Energy Transfer between Soil, Plants and Atmosphere), which verified the advantages of Conv-TALSTM in peak simulations. This study provides a direction for improving the accuracy, simplifying model structure and shortening calculation time in runoff simulations.

Attribution of Long-Term Evapotranspiration Trends in the Mekong River Basin with a Remote Sensing-Based Process Model

Using the Global Land Surface Satellite (GLASS) leaf area index (LAI), the actual evapotranspiration (ETa) and available water resources in the Mekong River Basin were estimated with the Remote Sensing-Based Vegetation Interface Processes Model (VIP-RS). The relative contributions of climate variables and vegetation greening to ETa were estimated with numerical experiments. The results show that the average ETa in the entire basin increased at a rate of 1.16 mm year−2 from 1980 to 2012 (36.7% of the area met the 95% significance level). Vegetation greening contributed 54.1% of the annual ETa trend, slightly higher than that of climate change. The contributions of air temperature, precipitation and the LAI were positive, whereas contributions of solar radiation and vapor pressure were negative. The effects of water supply and energy availability were equivalent on the variation of ETa throughout most of the basin, except the upper reach and downstream Mekong Delta. In the upper reach, climate warming played a critical role in the ETa variability, while the warming effect was offset by reduced solar radiation in the Mekong Delta (an energy-limited region). For the entire basin, the available water resources showed an increasing trend due to intensified precipitation; however, in downstream areas, additional pressure on available water resources is exerted due to cropland expansion with enhanced agricultural water consumption. The results provide scientific basis for practices of integrated catchment management and water resources allocation.

Detailed Geophysical Mapping and Hydrogeological Characterisation of the Subsurface for Optimal Placement of Infiltration-Based Sustainable Urban Drainage Systems

The continuous growth of cities in combination with future climate changes present urban planners with significant challenges, as traditional urban sewer systems are typically designed for the present climate. An easy and economically feasible way to mitigate this is to introduce a Sustainable Urban Drainage System (SUDS) in the urban area. However, the lack of knowledge about the geological and hydrogeological setting hampers the use of SUDS. In this study, 1315 ha of high-density electromagnetic (DUALEM-421S) data, detailed lithological soil descriptions of 614 boreholes, 153 infiltration tests and 250 in situ vane tests from 32 different sites in the Central Denmark Region were utilised to find quantitative and qualitative regional relationships between the resistivity and the lithology, the percolation rates and the undrained shear strength of cohesive soils at a depth of 1 meter below ground surface (m bgs). The qualitative tests enable a translation from resistivity to lithology as well as a translation from lithology to percolation rates with moderate to high certainty. The regional cut-off value separating sand-dominated deposits from clay-dominated deposits is found to be between 80 to 100 Ωm. The regional median percolation rates for sand and clay till is found to be 9.9 × 10−5 m/s and 2.6 × 10−5 m/s, respectively. The quantitative results derived from a simple linear regression analysis of resistivity and percolation rates and resistivity and undrained shear strength of cohesive soils are found to have a very weak relationship on a regional scale implying that in reality no meaningful relationships can be established. The regional qualitative results have been tested on a case study area. The case study illustrates that site-specific investigations are necessary when using geophysical mapping to directly estimate lithology, percolation rates and undrained shear strength of cohesive soils due to the differences in soil properties and the surrounding environment from site to site. This study further illustrates that geophysical mapping in combination with lithological descriptions, infiltration tests and groundwater levels yield the basis for the construction of detailed planning maps showing the most suitable locations for infiltration. These maps provide valuable information for city planners about which areas may preclude the establishment of infiltration-based SUDS.

Comprehensive evaluation on water resource carrying capacity in karst areas using cloud model with combination weighting method: a case study of Guiyang, southwest China

It is important to maintain the sustainable development of water resources. Objective assessment on water resource carrying capacity (WRCC) is beneficial to the formulation of scientific and reasonable water management practices. In view of the problem that evaluation indicators of WRCC cannot describe the fuzziness and randomness, a cloud model was introduced into regional WRCC assessment. This study selected a typical karst area (Guiyang) as the research object to study WRCC by using cloud model with combination weighting method. WRCC was assessed from the following five dimensions: water environment subsystem, social subsystem, economic subsystem, ecological subsystem, and humanities (water resource management and policy regulation) subsystem. In addition, evaluation results after normalizing all of indicators data were also calculated. And these two kinds of evaluation results were compared with that of technique of order preference similarity to the ideal solution (TOPSIS), finding that evaluation results of cloud model were consistent with that of TOPSIS method. The cloud model realizes the transformation from qualitative evaluation to quantitative evaluation, which overcome insufficiencies of traditional evaluation methods in considering fuzziness and randomness. Results showed that during the period of 2008-2017, the state of WRCC in Guiyang was improving year by year, increasing from the serious overload carrying capacity level in 2008 to the strong carrying capacity level in 2017 (serious overload-overload-critical-weak carrying capacity-strong carrying capacity). However, some certain evaluation indicators are still in danger situation, such as population natural growth rate and use of the fertilizer per unit cultivated area, which needs to be further enhanced and improved. Moreover, the contradiction among economic development, population growth, and water resources is becoming increasingly apparent. To ensure the effective utilization of water resources in Guiyang, reasonable policies and measures should be formulated and put into effect. Research results could provide certain reference for the sustainable development of regional water resources.

Leading edges in bioremediation technologies for removal of petroleum hydrocarbons

There is a worldwide concern regarding soil pollution caused by contamination of petroleum hydrocarbon, released during oil processing or production. Once a spill occurs, it disturbs the marine and freshwater ecosystem and greatly threatens human health. It usually requires complex technologies to remove it from soil. Petroleum hydrocarbons contain a range of chemicals which are extremely toxic and carcinogenic in nature. Although physical or chemical methods are widely employed for remediation, numerous studies revealed that bioremediation is a sustainable approach. Bioremediation is often preferred as clean and carbon-neutral solution. This review aims to provide series of sustainable solution for petroleum hydrocarbon degradation without exploiting the environment as well as opportunity to reuse treated media. Integrated and enhanced bioremediation technologies are more effective than natural degradation of petroleum hydrocarbons in terms of shorter time period and percent removal efficiency. It comprehensively illustrates bioremediation assisted with bacteria, fungi, and algae either by integrated technologies or by enhancing the process. Most recent application methods of petroleum hydrocarbon bioremediation (in situ and ex situ) are also reported. There is dire need to explore different cost-effective biotechnological resources for degradation of petroleum hydrocarbon by the screening of novel microbial strains or by the creation of genetically engineered bacteria to survive in harsh environment.

Comparative evaluation of VIIRS daily snow cover product with MODIS for snow detection in China based on ground observations

Accurate spatiotemporal information of snow cover not only is important for investigating the mechanisms of climate change but also greatly contributes to hydrological modelling in mountainous regions. The Suomi-National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) (referred to as VNP) daily snow cover product is recently released and expected to take place of Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products in near future. As an important addition to the widely used MODIS products, there is also an urgent need for a reliable accuracy evaluation and comparison of VNP for future large-scale daily snow cover mapping. This study for the first time evaluates the accuracy of VNP daily snow cover data in China using daily snow depth observations from 330 stations. The accuracy of VNP data is generally good with the averaged CK (Cohen's Kappa) and FS (F-Score) as high as 0.72 and 0.75, respectively, but considerably decreases to 0.50 and 0.52 for the Tibetan Plateau. VNP shows slightly better accuracy than MODIS TERRA for stations outside the Tibetan Plateau owing to its higher spatial resolution, but its accuracy is lower than TERRA for those within the Tibetan Plateau possibly due to its longer time interval between ground observation and satellite overpass time. By contrast, VNP shows much better accuracy than MODIS AQUA in China including both outside and within the Tibetan Plateau. This study provides important implications for optimal use of VNP and MODIS daily snow cover products in China, which may further contribute to more accurate snow variation information for climate analysis and cryospheric hydrological modelling.

Geomorphic Effects of a Dammed Pleistocene Lake Formed by Landslides along the Upper Yellow River

In a previous study two pairs of paleo-landslides within an 8 km reach of the upper Yellow River were studied and dated back to ca. 80 ka, however the relationship between these two pairs of paleo-landslides were not explored. This study inferred that the initial pair of landslides (Dehenglong and Suozi) appearing contiguously and forming an upstream 46 km-long lake along the river may be triggered by earthquake events from nearby capable faults. Subsequently, backwater inundating the valley floor as the dammed lake formed may cause shear stress of sediments lowered on steep slopes adjacent to the River, and eventually induce the other two additional landslides (Xiazangtan and Kangyang) ~8 km upstream. This could be inferred from two optically stimulated luminescence (OSL) samples yielding ca. 80 ka also, which were collected from asymmetric folds 10 to 30 cm in amplitude within the bedding plane between lake/lakeshore sediment and landslide mass at the front lobes of the two additional landslides. We estimated the maximum volume of this dammed lake was 38 km3 and may generate an outburst flood with an estimated peak discharge of 6.1 × 105 m3/s, which may cause massive geomorphic effects and potential disasters upstream and downstream. It is important to better understand the geomorphic process of this damming event in mountainous area with respect to reflecting tectonic uplift, paleoclimatic change and forecast and mitigate hazards on the northeast Tibetan Plateau.

Changes in Precipitation Extremes over the Source Region of the Yellow River and Its Relationship with Teleconnection Patterns

Precipitation extremes and their underlying causes are important processes to understand to plan appropriate adaptation measures. This paper presents an analysis of the spatiotemporal variability and trend of precipitation extremes in the important source region of the Yellow River and explores the connection to global teleconnection patterns and the 850-mb vector wind. Six indices for precipitation extremes were computed and analyzed for assessment of a changing regional climate. Results showed that these indices have a strong gradient from the northwest to the southeast part for the period 1961–2015, due to the great influence from the south-easterly summer monsoon flow. However, no statistically significant trends were found for the defined indices at the majority of stations, and their spatial distribution are noticed by irregularly mixed positive and negative changes except for the maximum number of consecutive wet days (CWD). Singular value decomposition analysis revealed that the precipitation extreme indices—including annual total precipitation when daily precipitation >95th percentile (R95p), annual count of days with daily precipitation ≥10 mm (R10mm), annual maximum consecutive 5-day precipitation (R5d), total precipitation divided by the number of wet days (SDII), and CWD—are negatively related to the El Nino-Southern Oscillation (NINO 3.4) in the first mode, and the maximum number of consecutive dry days (CDD) is positively related to the Scandinavian pattern in the second mode at 0.05 significance level. The 850-mb vector wind analysis showed that the southwestern monsoon originating from the Indian Ocean brings sufficient moisture to this region. Furthermore, the anti-cyclone in the western part of the North Pacific plays a significant role in the transport of moisture to the source region of the Yellow River. The links between precipitation extremes and teleconnection patterns explored in this study are important for better prediction and preparedness of climatic extremes.

Low-Carbon Concrete Based on Binary Biomass Ash-Silica Fume Binder to Produce Eco-Friendly Paving Blocks

The civil construction industry consumes huge amounts of raw materials and energy, especially infrastructure. Thus, the use of eco-friendly materials is indispensable to promote sustainable development. In this context, the present work investigated low-carbon concrete to produce eco-friendly paving blocks. The binder was defined according to two approaches. In the first, a binary binder developed with eucalyptus biomass ash (EBA) and silica fume (SF) was used, in total replacement for Portland cement. In the second, the mixture of residues was used as a precursor in alkali-activation reactions, forming alkali-activated binder. The experimental approach was carried out using five different mixtures, obtained by varying the amount of water or sodium hydroxide solution. The characterization of this new material was carried out using compressive strength, expandability, water absorption, deep abrasion, microstructural investigation, and organic matter degradation potential. The results showed that the EBA-SF system has a performance compatible with Portland cement when used as an alternative binder, in addition to functioning as a precursor to alkali-activated concrete. The blocks produced degraded organic matter, and this degradation is more intense with the incidence of UV. In this way, the EBA-SF binder can be successfully used for the manufacture of ecological paving blocks with low carbon emissions.

Predicting Urban Waterlogging Risks by Regression Models and Internet Open-Data Sources

In the context of climate change and rapid urbanization, urban waterlogging risks due to rainstorms are becoming more frequent and serious in developing countries. One of the most important means of solving this problem lies in elucidating the roles played by the spatial factors of urban surfaces that cause urban waterlogging, as well as in predicting urban waterlogging risks. We applied a regression model in ArcGIS with internet open-data sources to predict the probabilities of urban waterlogging risks in Hanoi, Vietnam, during the period 2012–2018 by considering six spatial factors of urban surfaces: population density (POP-Dens), road density (Road-Dens), distances from water bodies (DW-Dist), impervious surface percentage (ISP), normalized difference vegetation index (NDVI), and digital elevation model (DEM). The results show that the frequency of urban waterlogging occurrences is positively related to the first four factors but negatively related to NDVI, and DEM is not an important explanatory factor in the study area. The model achieved a good modeling effect and was able to explain the urban waterlogging risk with a confidence level of 67.6%. These results represent an important analytic step for urban development strategic planners in optimizing the spatial factors of urban surfaces to prevent and control urban waterlogging.

Flood hazard mapping and assessment in data-scarce Nyaungdon area, Myanmar

Torrential and long-lasting rainfall often causes long-duration floods in flat and lowland areas in data-scarce Nyaungdon Area of Myanmar, imposing large threats to local people and their livelihoods. As historical hydrological observations and surveys on the impact of floods are very limited, flood hazard assessment and mapping are still lacked in this region, making it hard to design and implement effective flood protection measures. This study mainly focuses on evaluating the predicative capability of a 2D coupled hydrology-inundation model, namely the Rainfall-Runoff-Inundation (RRI) model, using ground observations and satellite remote sensing, and applying the RRI model to produce a flood hazard map for hazard assessment in Nyaungdon Area. Topography, land cover, and precipitation are used to drive the RRI model to simulate the spatial extent of flooding. Satellite images from Moderate Resolution Imaging Spectroradiometer (MODIS) and the Phased Array type L-band Synthetic Aperture Radar-2 onboard Advanced Land Observing Satellite-2 (ALOS-2 ALOS-2/PALSAR-2) are used to validate the modeled potential inundation areas. Model validation through comparisons with the streamflow observations and satellite inundation images shows that the RRI model can realistically capture the flow processes (R² ≥ 0.87; NSE ≥ 0.60) and associated inundated areas (success index ≥ 0.66) of the historical extreme events. The resultant flood hazard map clearly highlights the areas with high levels of risks and provides a valuable tool for the design and implementation of future flood control and mitigation measures.

Particulate matter accumulation capacity of plants in Hanoi, Vietnam

Population growth, urbanization, environmental conditions and rapid development have caused particulate matter (PM) levels to rise above all national and international health standards during the last two decades in many South-East Asian countries. These PM levels needs to be reduced urgently as they increase the risk of cardiovascular and respiratory health problems for millions of people. Plants have shown to efficiently reduce PM in the air by accumulation on their leaves. In order to investigate which plant species accumulate most PM, we screened 49 common plant species for their PM accumulation capacity in one of the tropical cities with the highest PM concentrations of the world, Hanoi (Vietnam). Using this subset of plants, we tested if certain leaf characteristics (leaf hydrophilicity, stomatal densities and the specific leaf area) can predict the PM accumulation efficiency of plant species. Our results show that the PM accumulation capacity varies substantially among species and that Muntingia calabura accumulated most PM in our subset of plants. We observed that plants with hydrophilic leaves, a low specific leaf area and a high abaxial stomatal density accumulated significantly more PM. Plants with these characteristics should be preferred by urban architects to reduce PM levels in tropical environments.

Validation of a Novel, Shear Reynolds Number Based Bed Load Transport Calculation Method for Mixed Sediments against Field Measurements

In this study, the field measurement-based validation of a novel sediment transport calculation method is presented. River sections with complex bed topography and inhomogeneous bed material composition highlight the need for an improved sediment transport calculation method. The complexity of the morphodynamic features (spatially and temporally varied bed material) can result in the simultaneous appearance of the gravel and finer sand dominated sediment transport (e.g., parallel bed armoring and siltation) at different regions within a shorter river reach. For the improvement purpose of sediment transport calculation in such complex river beds, a novel sediment transport method was elaborated. The base concept of it was the combined use of two already existing empirical sediment transport models. The method was already validated against laboratory measurements. The major goal of this study was the verification of the novel method with a real river case study. The combining of the two sediment transport models was based on the implementation of a recently presented classification method of the locally dominant sediment transport nature (gravel or sand transport dominates). The results were compared with measured bed change maps. The verification clearly referred to the meaningful improvement in the sediment transport calculation by the novel manner in the case of spatially varying bed content.

Hydrologic Modeling for Sustainable Water Resources Management in Urbanized Karst Areas

The potential of karst aquifers as a drinking water resource is substantial because of their large storage capacity gained in the course of carbonate dissolution. Carbonate dissolution and consequent development of preferential paths are also the reasons for the complex behavior of these aquifers as regards surface and underground flow. Hydrological modeling is therefore of paramount importance for an adequate assessment of flow components in catchments shaped on karsts. The cross tabulation of such components with geology, soils, and land use data in Geographic Information Systems helps decision makers to set up sustainable groundwater abstractions and allocate areas for storage of quality surface water, in the context of conjunctive water resources management. In the present study, a hydrologic modeling using the JAMS J2000 software was conducted in a karst area of Jequitiba River basin located near the Sete Lagoas town in the state of Minas Gerais, Brazil. The results revealed a very high surface water component explained by urbanization of Sete Lagoas, which hampers the recharge of 7.9 hm³ yr⁻¹ of storm water. They also exposed a very large negative difference (−8.3 hm³ yr⁻¹) between groundwater availability (6.3 hm³ yr⁻¹) and current groundwater abstraction from the karst aquifer (14.6 hm³ yr⁻¹), which is in keeping with previously reported water table declines around drilled wells that can reach 48 m in old wells used for public water supply. Artificial recharge of excess surface flow is not recommended within the urban areas, given the high risk of groundwater contamination with metals and hydrocarbons potentially transported in storm water, as well as development of suffosional sinkholes as a consequence of concentrated storm flow. The surface component could however be stored in small dams in forested areas from the catchment headwaters and diverted to the urban area to complement the drinking water supply. The percolation in soil was estimated to be high in areas used for agriculture and pastures. The implementation of correct fertilizing, management, and irrigation practices are considered crucial to attenuate potential contamination of groundwater and suffosional sinkhole development in these areas.

A Bayesian Network-Based Integrated for Flood Risk Assessment (InFRA)

Floods are natural disasters that should be considered a top priority in disaster management, and various methods have been developed to evaluate the risks. However, each method has different results and may confuse decision-makers in disaster management. In this study, a flood risk assessment method is proposed to integrate various methods to overcome these problems. Using factor analysis and principal component analysis (PCA), the leading indicators that affect flood damage were selected and weighted using three methods: the analytic hierarchy process (AHP), constant sum scale (CSS), and entropy. However, each method has flaws due to inconsistent weights. Therefore, a Bayesian network was used to present the integrated weights that reflect the characteristics of each method. Moreover, a relationship is proposed between the elements and the indicators based on the weights called the Integrated Index for Flood Risk Assessment (InFRA). InFRA and other assessment methods were compared by receiver operating characteristics (ROC)-area under curve (AUC) analysis. As a result, InFRA showed better applicability since InFRA was 0.67 and other methods were less than 0.5.

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region

Spatial patterns of water quality trends for 45 stations in control units of the Shandong Province, China during 2009–2017 were examined by a non-parametric seasonal Mann-Kendall’s test (SMK) for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), permanganate index (COD_Mn), total phosphorus (TP) and ammonia nitrogen (NH₃-N). The DO concentration showed significant upward trends at approximately half of the stations, while other parameters showed significant downward trends at more than 40% of stations. The stations with downward trends presented significant spatial autocorrelation, and were mainly concentrated in the northwest and southwest regions. The relationship between the landscape characteristics and water quality was explored using stepwise multiple regression models, which indicated the water quality was better explained using landscape pattern metrics compared to the percentage of land use types. Decreased mean patch area and connectedness of farmland will promote the control of BOD, COD and COD_Mn, whereas the increased landscape percentage of urban areas were not conducive to the water quality improvement, which suggested the sprawling of farmland and urban land was not beneficial to pollution control. Increasing the grassland area was conducive to the reduction of pollutants, while the effect of grassland fragmentation was reversed.

Effects of Temperature Change on the Soil Water Characteristic Curve and a Prediction Model for the Mu Us Bottomland, Northern China

The soil-water characteristic curve (SWCC) is the basis for obtaining the hydraulic conductivity parameters of a soil as well as for using soil water and heat transport models. At present, the curve can be obtained by two methods: by direct measurement and by empirical formula. Direct measurement is both difficult and time-consuming. By contrast, fitting the SWCC with a suitable empirical formula is stable and convenient. The van Genuchten (VG) model has the advantage of universal applicability due to its use of a statistical aperture distribution model for estimating hydraulic conductivity. This study selected the Mu Us Bottomland as a study area. Data on the water content and water potential of undisturbed soil from this site were obtained with a Ku-pF instrument and a self-designed soil column experiment with temperature settings of 13 °C, 18 °C, 23 °C, 27 °C, and 30 °C. The variation of four main parameters in the VG model with temperature was analyzed based on thermodynamic theory and considering the effect of temperature on soil capillary pressure via its effects on surface tension and contact angle. A prediction model for the soil-water characteristic curve of the Mu Us Bottomland was then constructed, and its applicability was further analyzed. The temperature dependence of the SWCC demonstrated here provides an important scientific basis for agricultural production, farmland water conservancy, and the design of soil and water conservation engineering projects.

Effects of Bridge Piers on Flood Hazards: A Case Study on the Jialing River in China

Bridge piers on river channels can cause obstacles for flood flow by reducing the cross-sectional area and inducing local eddy currents and high flow velocities, which may destroy hydraulic structures. A two-dimensional numerical model was used to investigate the effects of bridge piers on river flood hazards in the Jialing River, China. For the modeling, Mike 21 FM was used, which is an unstructured mesh and finite volume model that solves the shallow water equations. The numerical model was validated with collected historical flood traces, and sensitivity analyses identified the effects of the Manning coefficient and the dependence on the grid size. The influence of backwater effects on the flow field was analyzed by comparing numerical results with and without piers. The results showed that the most significant impacts were caused by the Fengxian Bridge. The maximum water level rise was about 1 m and the maximum velocity near this bridge decreased by 22.77% for a 10-year flood. We found that the top elevations of planned levees near the bridges must be increased by 0.15–0.36 m. The influence of bridge piers on the flood velocity field is more complex. These findings will help flood hazard management in this river and provides a reference for similar projects.

Climate change impact on fluvial flooding in the Indian sub-basin: A case study on the Adyar sub-basin

Flooding is one of the most disastrous global hazards, which has been occurring more frequently in recent times. It is observed that climate change is likely to increase the intensity and the frequency of floods and river basins have become more vulnerable to fluvial flooding. In this study, the impact of climate change on fluvial flooding was analyzed over the Adyar sub-basin. This study applied statistically downscaled Global Climate Model (GCM) data in a CMIP5 dataset of IPCC Assessment Report 5 (AR5). Based on the performance to simulate the observed climate, four GCMs, namely, cesm1-cam5, mpi-esm-mr, ncar-ccsm4, and bnu-esm, for RCP 4.5 were selected for projections of the future scenario. The Intensity-Duration-Frequency (IDF) curves for the past and future scenarios were derived from the IMD-observed and GCM-projected rainfall data. Integrated flood modeling was performed with hydrologic (HEC-HMS) and hydraulic (HEC-RAS) models. Finally, in order to visualize the inundation areas according to the future climate projection, flood inundation maps were prepared geospatially using the ArcGIS software. For the 100-year return period, the results predict that the peak discharge for the future climate scenario would increase by 34.3%–91.9% as compared to the present climate scenario. Similarly, the future projections show an increase in the flooded area ranging from 12.6% to 26.4% based on GCMs. This simulation helps in understanding the flood risk over the Adyar sub-basin under the changing climate and the requirement for the regulation of developmental activities over the flood-prone areas.

Farm ponds in southern China: Challenges and solutions for conserving a neglected wetland ecosystem

Farm ponds, which are sometimes numerous and widely distributed in agricultural regions, have faced widespread degradation in recent decades. Although conservation strategies for these biodiversity hotspots have gradually increased, appropriate approaches for developing country contexts are lacking. Farm ponds provided hydrologic, biogeochemical, and socioeconomic benefits to southern China for thousands of years, but they are facing contemporary threats and management challenges, including (1) inadequate planning in terms of construction and conservation regulations; (2) rural nonpoint source and mini-point source pollution; (3) climate change induced abnormalities in the hydroperiod and disturbance to wildlife; (4) invasive species; and (5) inadequate social and political capacity to consider ecological conservation. Because farm ponds function as wetland complexes that are embedded within or integral to larger ecosystems, their conservation requires collaborative efforts over scales ranging from within-pond to regional. We highlight approaches that build public awareness and involve inventory maps as a basis. Policies that integrate top-down regulation and bottom-up engagement and emphasize sustainable management and utilization are recommended to ensure the effectiveness and continuous improvement of conservation programs. Techniques that involve interconnected smart sensors, volunteering and citizen science, and integrated process-based modeling are preferred when conducting comprehensive descriptions of the pond landscape, numerical assessments on their ecosystem services, and associated conservation cost analyses. Nature-based solutions are increasingly recognized as an important opportunity for coping with water-related crises. This paper presents the first synthetic perspective on the ecological roles of farm ponds in agriculturally dominated developing countries. The analytical framework and conservation suggestions are referential to sustainable rural development and the management of other small, scattered wetlands.

A Novel Approach for Delineation of Homogeneous Rainfall Regions for Water Sensitive Urban Design—A Case Study in Southeast Queensland

The delineation of homogeneous regions is primarily based on long-term overall rainfall characteristics and therefore does not necessarily consider the homogeneity of event-based rainfall characteristics. However, event-based rainfall characteristics including antecedent dry days, rainfall intensity, total rainfall and total duration of rainfall events are critical for Water Sensitive Urban Design (WSUD). Accordingly, this study presents a novel approach to objectively identify homogeneous rainfall regions based on event-based rainfall characteristics. This approach uses cluster analysis and Hosking–Wallis heterogeneous tests collectively to test the homogeneity of event-based rainfall characteristics. A case study conducted for southeast Queensland (SEQ), Australia is also presented in this article. This study compares the results of the novel modified approach against results of the conventional approach for the delineation of homogeneous regions. It was evident from the results that the entire SEQ could be treated as a homogeneous rainfall region based on the conventional approach. In contrast, based on the modified approach, the coast and the inland of SEQ were identified as separate homogeneous regions. Further, antecedent dry days and rainfall intensity were recognized as the deciding rainfall characteristics in the delineation of homogeneous rainfall regions.

A Simple Early Warning System for Flash Floods in an Ungauged Catchment and Application in the Loess Plateau, China

Under climate change, flash floods have become more frequent and severe, and are posing a danger to society, especially in the ungauged catchments. The objective of this paper, is to construct a simple and early warning system, serving for flash floods risk management in the ungauged catchments of the Loess Plateau in China, and offer a reference for flash flood warning in other areas in the world. Considering the absence of hydrological data in the ungauged catchments, the early warning system for flash floods is established by combining the regional or watershed isograms of hydrological parameters and local empirical formulas. Therein, rainfall and water stage/flow are used as warning indices for real-time risk estimation of flash flood. For early warning, the disaster water stage was first determined according to the protected objects (e.g., residents and buildings), namely the critical water stage. The critical flow (flow threshold), was calculated based on the water stage, and the established relationship between water stage and flow using the cross-sectional measured data. Then, according to the flow frequency curve of the design flood, the frequency of critical flow was ascertained. Assuming that the rainfall and the flood have the same frequency, the critical rainfall threshold was calculated through the design rainstorm with the same frequency of the design flood. Due to the critical rainfall threshold being sensitive with different soil conditions, the design flood and frequency curve of flood flow were calculated under different soil conditions, and thus the rainfall threshold was given under different soil condition for early warning of the flash flood disaster. Taking two sections in Zichang County (within the Loess Plateau) as an example, we set the rainfall and water stage/flow thresholds to trigger immediate or preparation signals for the migration of the population along the river. The application of this method to the 7.26 flood events in 2017 in China, shows that the early warning system is feasible. It is expected that this simple early warning system can provide early warnings of flash floods in ungauged catchments in the Loess Plateau and other similar areas.

Update of Early Warning Indicators of Flash Floods: A Case Study of Hunjiang District, Northeastern China

The China flash flood investigation and evaluation database (CFFIED) covers important information needed for China’s flash flood warning. This paper uses a statistical induction method, inference formula method and standardized unit hydrograph method to explore its principle, characteristics, and key steps. Then based on the field investigation and the latest data on the flash flood, the Hunjiang District in northeastern China was selected as the research area. Firstly, three typical riverside villages, Xiangmo-1 and Sanchahe-3, Shangqing-4, were screened, and the flash flood warning indicators (e.g., water level, flow rate, critical rainfall) in the CFFIED were updated. Then, the maximum error of the flood peak, estimated by the inference formula method and the water level flow relationship method, is only 10.6%, which indicates that the predicted flood peak flow has high credibility and can check and identify the early warning index; the Manning formula is more accurate in calculating the water level flow relationship. However, the calculated ratio is lower and the roughness is higher, and the flow is smaller under the same water level. Finally, the updated flash flood warning indicators were obtained in the Hunjiang District, which improves the accuracy of the flash flood warning, and provides a reference for updating the early warning indicators in other areas.

Contribution of Excessive Supply of Solid Material to a Runoff-Generated Debris Flow during Its Routing Along a Gully and Its Impact on the Downstream Village with Blockage Effects

On 8 August 2017, a runoff-generated debris flow occurred in the Puge County, Sichuan Province of southwestern China and caused huge property damage and casualties (25 people died and 5 people were injured). Emergency field investigations found that paddy fields, dry land, residential buildings and roads suffered different degrees of impact from the debris flow. This paper reveals the formation process of the debris flow by analyzing the characteristics of rainfall precipitation and sediment supply conditions in the study area and it approaches the practical application of hazard prevention and mitigation constructions. Doppler weather radar analysis indicates that a very high intensity rainfall occurred in the middle and upper zones of the basin, illustrating the importance of enhancing rainfall monitoring in high-altitude areas. The abundant supply of deposits in gully channels is among the significant causes of a transformation from mountain floods to large-scale debris flows. It was also found that the two culverts played an important role in the movement affecting the processes of debris flows which has substantially aggravated the destructive outcome. The excessive supply of solid material and local blockage with outburst along a gully must receive significant attention for the prediction of future debris flows, hazard prevention and mitigation measures.

Generation of Monthly Precipitation Climatologies for Costa Rica Using Irregular Rain-Gauge Observational Networks

Precipitation climatologies for the period 1961–1990 were generated for all climatic regions of Costa Rica using an irregular rain-gauge observational network comprised by 416 rain-gauge stations. Two sub-networks were defined: a high temporal resolution sub-network (HTR), including stations having at least 20 years of continuous records during the study period (157 in total); and a high spatial resolution sub-network (HSR), which includes all HTR-stations plus those stations with less than 20 years of continuous records (416 in total). Results from the kriging variance reduction efficiency (KRE) objective function between the two sub-networks, show that ordinary kriging (OK) is unable to fully explain the spatio-temporal variability of precipitation within most climatic regions if only stations from the HTR sub-network are used. Results also suggests that in most cases, it is beneficial to increase the density of the rain-gauge observational network at the expense of temporal fidelity, by including more stations even though their records may not represent the same time step. Thereafter, precipitation climatologies were generated using seven deterministic (IDW, TS2, TS2PARA, TS2LINEAR, TPS, MQS and NN) and two geostatistical (OK and KED) interpolation methods. Performance of the various interpolation methods was evaluated using cross validation technique, selecting the mean absolute error (MAE) and the root-mean square error (RMSE) as agreement metrics. Results suggest that IDW is marginally superior to OK and KED for most climatic regions. The remaining deterministic methods however, considerably deviate from IDW, which suggests that these methods are incapable of properly capturing the true-nature of spatial precipitation patterns over the considered climatic regions. The final generated IDW climatology was then validated against the Global Precipitation Climatology Centre (GPCC), Climate Research Unit (CRU) and WorldClim datasets, in which overall spatial and temporal coherence is considered satisfactory, giving assurance about the use this new climatology in the development of local climate impact studies.

Permeable Pavements Life Cycle Assessment: A Literature Review

The number of studies involving life cycle assessment has increased significantly in recent years. The life cycle assessment has been applied to assess the environmental performance of water infrastructures, including the environmental impacts associated with construction, maintenance and disposal, mainly evaluating the amount of greenhouse gas emissions, as well as the consumption of energy and natural resources. The objective of this paper is to present an overview of permeable pavements and show studies of life cycle assessment that compare the environmental performance of permeable pavements with traditional drainage systems. Although the studies found in the literature present an estimate of the sustainability of permeable pavements, the great heterogeneity in the evaluation methods and results is still notable. Therefore, it is necessary to homogenize the phases of goal and scope, inventory analysis, impact assessment and interpretation. It is also necessary to define the phases and processes of the evaluation, as well as the minimum amount of data to be considered in the modelling of life cycle assessment, in order to avoid heterogeneity in the functional units and other components. Thus, more consistent results will lead to a real evaluation of the environmental impacts caused by permeable pavements. Life cycle assessment studies are essential to guide planning and decision-making, leading to systems that consider increasing water resources and reducing natural disasters and environmental impacts.

Analysis of Flood Risk of Urban Agglomeration Polders Using Multivariate Copula

Urban agglomeration polders (UAPs) are often used to control flooding in eastern China. The impacts of UAPs on individual flood events have been extensively examined, but how flood risks are influenced by UAPs is much less examined. This study aimed to explore a three-dimensional joint distribution of annual flood volume, peak flow and water level to examine UAPs’ impact on flood risks based on hydrological simulations. The dependence between pairwise hydrological characteristics are measured by rank correlation coefficients and graphs. An Archimedean Copula is applied to model the dependence structure. This approach is applied to the Qinhuai River Basin where UAPs are used proactively for flood control. The result shows that the Frank Copula can better represent the dependence structure in the Qinhuai River Basin. UAPs increase risks of individual flood characteristics and integrated risks. UAPs have a relatively greater impact on water level than the other two flood characteristics. It is noted that the impact on flood risk levels off for greater floods.