Search Results (16)

Soil erosion is a global environmental problem, and soil conservation is the prevention of soil loss from erosion. The Ten Kongduis (kongdui is the translation of “short-term flood gullies” in Mongolian) are ten tributaries in the upper Inner Mongolia section of the Yellow River Basin. The study of the spatial and temporal variability in soil conservation in the Ten Kongduis is of extraordinary scientific significance both in terms of the discipline and for the ecological and environmental management of the region. With the InVEST model, the characteristics of the spatial and temporal variations in soil conservation service in the Ten Kongduis since 2000 and how rainfall and land use have influenced soil conservation were analyzed. The results show that both avoided erosion and avoided export varied considerably between years. The minimum values of avoided erosion and avoided export were both in 2015, with values of 17.59 × 10⁶ t and 0.92 × 10⁶ t, respectively. The maximum value of avoided erosion was 57.03 × 10⁶ t in 2020 and that of avoided export was 4.08 × 10⁶ t in 2000. Spatially, avoided export was primarily found in the upper reaches of the east–central portion of the study area, and avoided erosion, with values of >40 t·(ha·yr)⁻¹, was in the upper east–central portion of the study area, followed by the upper west–central portion. The difference between upstream and downstream was larger in the western part of the study area. The effect of rainfall was dominant and positive in both avoided erosion and avoided export. The relationships between the rain erosivity factor and the values of avoided erosion and avoided export were significantly positive. Where more erosion occurs, more erosion is retained. Soil that has been eroded away from slopes under vegetation or other water conservation measures may not necessarily be transported to the stream channel in the current year. These conclusions will help us to have a clearer understanding of where sediments are generated and transported and provide a scientific basis for soil and water conservation and ecosystem safety management of watersheds. Full article

Watershed hydrological modeling methods are currently the predominant approach for flood forecasting. Digital elevation model (DEM) data, a critical input variable, significantly influence the accuracy of flood simulations, primarily due to their resolution. However, there is a paucity of research exploring the relationship between DEM resolution and flood simulation accuracy. This study aims to investigate this relationship by examining three watersheds of varying scales in southern Jiangxi Province, China. Utilizing the Liuxihe model, a new-generation physically based distributed hydrological model (PBDHM), we collected and collated data, including DEM, land use, soil type, and hourly flow and rainfall data from monitoring stations, covering 22 flood events over the last decade, to conduct model calibration and flood simulation. DEM data were processed into seven resolutions, ranging from 30 m to 500 m, to analyze the impact of DEM resolution on flood simulation accuracy. The results are as follows. (1) The Nash–Sutcliffe efficiency coefficients for the entire set of flood events were above 0.75, demonstrating the Liuxihe model’s strong applicability in this region. (2) The DEM resolution of the Anhe and Dutou watersheds lost an average of 7.9% and 0.8% accuracy when increasing from 30 m to 200 m, with further losses of 37.9% and 10.7% from 200 m to 300 m. Similarly, the Mazhou watershed showed an average of 8.4% accuracy loss from 30 m to 400 m and 20.4% from 400 m to 500 m. These results suggest a threshold where accuracy sharply declines as DEM resolution increases, and this threshold rises with watershed scale. (3) Parameter optimization in the Liuxihe model significantly enhanced flood simulation accuracy, effectively compensating for the reduction in accuracy caused by increased DEM resolution. (4) The optimal parameters for flood simulation varied with different DEM resolutions, with significant changes observed in riverbed slope and river roughness, which are highly sensitive to DEM resolution. (5) Changes in DEM resolution did not significantly impact surface flow production. However, the extraction of the water system and the reduction in slope were major factors contributing to the decline in flood simulation accuracy. Overall, this study elucidates that there is a threshold range of DEM resolution that balances data acquisition efficiency and computational speed while satisfying the basic requirements for flood simulation accuracy. This finding provides crucial decision-making support for selecting appropriate DEM resolutions in hydrological forecasting. Full article

Urban rainstorms and flood disasters are the most common and severe environmental problems worldwide. Many factors influence rain-flood control simulation, forming a complex network system of interconnected and mutually constraining elements. In terms of spatial scale selection, existing research on rain-flood disaster risk largely relies on a single-scale infrastructure index system and has not yet focused on urban “gray-green-blue” spatial scale simulations for rain-flood storage. Regarding research methodology, applying system dynamics methods to the simulation of rain-flood storage and disaster prevention planning in watershed cities is still in its initial stages. System dynamics models can simulate the feedback interactions among various sub-elements in the coupled mega-system, fully addressing complex issues within the system structure that involve multiple variables, non-linear relationships, and numerous feedback loops, thereby compensating for the inadequacies of traditional linear models in the collaborative management of rain-flood risks. Taking the Changsha Guitang River Basin as an example, this paper constructs a system dynamics model covering four dimensions: natural environment, socio-economics, internal structure, and policy development. It aims to derive the optimal planning scheme for gray-green-blue spatial coordination in rain-flood storage by weighing four different development scenarios. The simulation results show: (1) Simply changing the surface substrates without considering rainwater discharge and the plan that emphasizes the construction of municipal drainage facilities will see the capacity gap for rain-flood storage-space construction continue to widen by 2035. This indicates that the plans mentioned above will struggle to bear the socio-economic losses cities face during rain-flood disasters. (2) The plan of combining gray and green infrastructures sees the rain-flood storage construction capacity turn from negative to positive from 2024, rising to 52.259 billion yuan by 2035. This reflects that the plan can significantly reduce the rainwater volume in the later stages of low-impact development infrastructure construction, mitigate rain-flood disaster risks, and reduce government investment in rain-flood disaster risk management, making it a relatively excellent long-term rain-flood storage space planning option. (3) The rain-flood regulation space planning scheme, under the combined effect of the urban “gray-green-blue” network system, sees the capacity for rain-flood storage construction turn positive a year earlier than the previous plan, reaching 54.232 billion yuan by 2035. This indicates that the scheme can not only effectively respond to extreme flood and rainstorm disasters but also maintain ecological environment benefits and mitigate the socio-economic losses caused by disasters, making it the optimal choice for future government disaster management planning. The research results provide a theoretical framework and practical insights for territorial spatial planning, rain-flood control management, and resilient city construction in watershed areas. Full article

Global Climate change (CC) is featured by long-term changes in the mean values of climatic parameters (predominantly mean temperature) and in the profile of extreme weather events (e.g., increase in frequency, intensity, lengthening, and persistence). These climatic changes are supposed to have a deterioration impact on forest fire and flood disasters. Greece, an east Mediterranean country, is featured by a wide variety of micro-climates due to its unique geographical diversity, including hot and dry summers in the eastern part of the country (where a large amount of precipitation falls in the form of showers and thunderstorms) and wet winters in the western part. The combination of certain climatic zones with unfavorable land use and land cover changing patterns has resulted in several regions being prone to flooding and forest fires. The authors, based on relevant records, consider central and south Greece as flood and forest fire hotspots and attempt to: (a) present scientific estimations of local climate changes; (b) outline recent trends in the number of respective disasters and the amount of losses in these regions; (c) address recent changes in local climatic factors that might have influenced flood and forest fire hazard and risk in these regions; and (d) study the perceptions of the lay public and management authorities regarding the accountability of CC for flood and forest fire risk and hazard changes. The results show the variability of climate changes between neighboring areas, which directly affect the risk of forest fires and floods. Especially since the beginning of the 21st century, central Greece has been experiencing dramatic increases in both risks, while in south Greece the latter remain relatively stable. With regard to the perceptions of citizens and management authorities, the mental connection of local CC with forest fires and floods is still weak if not totally missing. Since knowledge and perceptions of the local “history” of forest fires and floods and the interconnections with CC by region is very important for the local communities to take appropriate mitigation and adaptation measures, this paper outlines a methodological path for similar studies to be conducted also in other regions of the Mediterranean basin and beyond. Full article

Crop simulation models can be effective tools to assist with optimization of resources for a particular agroecological zone. The goal of this study was to determine the influence of N rates with different timing of application to wheat crop using prominent varieties using the CSM-CERES-Wheat model of the decision support system for agrotechnology transfer (DSSAT). Data were focused for yield traits, i.e., number of tillers, number of grains, grain weight, grain yield, biomass, and grain N content. To test the applicability of the CSM-CERES-Wheat version 4.7.5 model for agroclimatic conditions of Peshawar, Pakistan, experimental data from two years of experiments (2016–17 and 2017–18) were used for model calibration and evaluation. The simulation results of two years agreed well with field measured data for three commercial varieties. The model efficiency (R²) for wheat varieties was above 0.94 for variables tiller number per unit area (m⁻²), number of grains (m⁻²) and number of grains (spike⁻¹), 1000 grain weight (mg), biomass weight (kg ha⁻¹), grain yield (kg ha⁻¹), and harvest N content (kg ha⁻¹). Statistics of cultivars indicated that yield traits, yield, and N can be simulated efficiently for agroecological conditions of Peshawar. Moreover, different N rates and application timings suggested that the application of 140 kg N ha⁻¹ with triple splits timings, i.e., 25% at the sowing, 50% at the tillering, and 25% at the booting stage of the crop, resulted in the maximum yield and N recovery for different commercial wheat varieties. Simulated N losses, according to the model, were highly determined by leaching for experimental conditions where a single N application of 100% or existing double splits timing was applied. The study concluded that 140 kg N ha⁻¹ is most appropriate for wheat crop grown on clay loam soils under a flood irrigation system. However, the N fertilizer has to be given in triple splits of a 1:2:1 ratio at the sowing, tillering, and booting stages of the crop growth. Full article

Water productivity of rice is imperative for global water security. Currently, water saving management techniques have been proposed and applied to rice systems. The crop water stress index (CWSI) is a major index for evaluating crop water use. The utility of the CWSI in rice in a humid temperate climate has been given little attention. Previous studies have focused on upland crops and readily available constant reference baselines, primarily the water stressed baseline (WSB), which does not inherently reflect transpiration flux. This study examined the performance of the estimated non-water stressed baseline (NWSB) and WSB for rice in a humid climate and the CWSI sensitivity under variable reference baseline scenarios in a 2-year pot trial under phytotron and field environment conditions with two rice genotypes (IRAT109 and Takanari) in a flooded (FL) and aerobic (AR) water regime. We observed that the dynamics of CWSI is dependent not only on the water regimes but could be strongly influenced by genotype sensitivity to vapor pressure deficit (VPD). A higher slope (pooled data) in the field environment (−5.68 °C kPa⁻¹) compared to the phytotron (−3.04 °C kPa⁻¹) reflected transpiration water loss sensitivity to VPD thresholds. Further studies with diverse rice germplasms to explore generalizability to field conditions and reformulation of reference baselines considering the VPD threshold sensitivity could prove to be significant. Full article

The variability of climate, increase in population, and lack of territorial plans in Costa Rica have caused intense disasters with human and economic losses. In 2016, Hurricane Otto hit the country’s northern area, leaving substantial damages, including landslides, debris flows, and flooding. The present study evaluated different scenarios to estimate flooded areas for Newtonian (clean water), and non-Newtonian flows with volumetric sediment concentrations (Cv) of 0.3, 0.45, 0.55, and 0.65 using Hydro-Estimator (HE), rain gauge station, and the 100-year return period event. HEC–HMS modeled the rainfall products, and FLO-2D modeled the hydrographs and Cv combinations. The simulation results were evaluated with continuous statistics, contingency table, Nash Sutcliffe Efficiency, measure of fit (F), and mean absolute differences (E) in the floodplains. Flow depths, velocities, and hazard intensities were obtained in the floodplain. The debris flood was validated with field data and classified with a Cv of 0.45, presenting lower MAE and RMSE. Results indicated no significant differences in flood depths between hydrological scenarios with clean-water simulations with a difference of 8.38% in the peak flow. The flood plain generated with HE rainfall and clear-water condition presented similar results compared to the rain gauge input source. Additionally, hydraulic results with HE and Cv of 0.45 presented E and F values similar to the simulation of Cv of 0.3, demonstrating that the HE bias did not influence the determination of the floodplain depth and extent. A mean bias factor can be applied to a sub-daily temporal resolution to enhance HE rain rate quantifications and floodplain determination. Full article

Regular features of ground and surface waters affected by drainage from mine waste include their acidity and elevated concentrations of dissolved metals, with their attendant negative effects on drinking water quality and aquatic life. One parameter that aids in buffering these waters against acidity and sustains aquatic life is dissolved inorganic carbon (DIC). In this study, the chemical and isotopic (δ¹³C) composition of primary calcite and DIC (δ¹³C_DIC) in groundwater and surface waters within and downstream, respectively, of abandoned Cu–W–F skarn tailings at Yxsjöberg, Sweden, were used to trace the biogeochemical processes controlling their respective δ¹³C_DIC signatures. In addition, the δ¹³C signatures of the inorganic (carbonate) fractions of the tailings were used to verify the formation of secondary carbonates within the tailings. Lower average δ¹³C values of the carbonate fractions (δ¹³C_carb = −2.7‰) relative to those of the primary calcite (δ¹³C = +0.1‰) from the orebodies from which the tailings originated pointed to the precipitation of secondary carbonates. These lower δ¹³Ccarb signatures were assumed to represent mixed-source C signals involving isotopically light CO₂ from the atmosphere, the degradation of organic matter in the upper part of the tailings and HCO₃⁻ from calcite dissolution. The groundwater δ¹³C_DIC values (−12.6‰ to −4.4‰) were far lower than the hypothetical range of values (−4.6‰ to +0.7‰) for primary calcite and secondary carbonate dissolution. These signatures were attributed to carbonate (calcite and secondary carbonate) dissolution and the degradation of dissolved organic carbon (DOC) from various organic sources such as peat underneath the tailings and the surrounding forests. Downstream surface water samples collected in May had low δ¹³C_DIC values (−16‰) and high DOC (14 mg C/L) compared to the groundwater samples. These signatures represented the oxidation of the DOC from the wash out of the mires and forests during the snowmelt and spring flood. The DOC and δ¹³C_DIC values of the surface waters from June to September ranged from 6–15 mg·C/L and −25‰ to −8.6‰, respectively. These signatures were interpreted to reflect mixed C sources, including carbonate dehydration by acidity from Fe³⁺ hydrolysis due to the mixing of groundwater with surface waters and the subsequent diffusive loss of CO_{2 (g)}, aquatic photosynthesis, photooxidation, DOC degradation, as well as microbial respiration. Although the ¹³C_DIC signatures of the downstream surface waters seemed to be seasonally controlled and influenced by variable groundwater contributions, the lack of data with respect to DIC concentrations, coupled with multiple potential biogeochemical processes that could influence the DIC pool and ¹³C_DIC values, made it difficult to identify the major regulating process of the ¹³C_DIC signatures. Therefore, other complimentary isotopes and elemental concentrations are recommended in order to decipher the dominant biogeochemical process. Full article

The Viola epipsila-V. palustris complex is a highly taxonomically complicated group of species in its entire circumboreal range of distribution. Habitat loss, forest flooding, and hybridization could lead to the extinction of V. epipsila. A hybrid index and principal component analysis (PCA) were used to select qualitative and quantitative morphological features to distinguish parent species and hybrids, inter simple sequence repeat (ISSR) markers to determine the genetic diversity of the populations, flow cytometry to estimate the genome size (GS), and non-coding chloroplast DNA (cpDNA) regions to indicate the directions of crosses. All taxa are very morphologically variable, and their features can change within a season. The most stable feature is the distance of the bracts on the pedicel from the rhizome. The genetic diversity of all taxa populations is low and highly influenced by selfing and vegetative propagation. The population structure is differentiated: populations of V. epipsila or V. palustris, mixed populations with both parent species, F1 hybrids and populations with introgressive forms occur in different regions. The interspecific GS variation corresponds to the ploidy level (4x = 2.52 pg, 8x = 4.26 pg, 6x = 3.42 pg). Viola epipsila is the mother plant of the hybrids. Research has shown the risk of V. epipsila extinction in Central Europe and the importance of local populations in studying the role of hybridization in reducing/maintaining/increasing biodiversity. Full article

Social vulnerability indicators seek to identify populations susceptible to hazards based on aggregated sociodemographic data. Vulnerability indices are rarely validated with disaster outcome data at broad spatial scales, making it difficult to develop effective national scale strategies to mitigate loss for vulnerable populations. This paper validates social vulnerability indicators using two flood outcomes: death and damage. Regression models identify sociodemographic factors associated with variation in outcomes from 11,629 non-coastal flood events in the USA (2008–2012), controlling for flood intensity using stream gauge data. We compare models with (i) socioeconomic variables, (ii) the composite social vulnerability index (SoVI), and (iii) flood intensity variables only. The SoVI explains a larger portion of the variance in death (AIC = 2829) and damage (R² = 0.125) than flood intensity alone (death—AIC = 2894; damage—R² = 0.089), and models with individual sociodemographic factors perform best (death—AIC = 2696; damage—R² = 0.229). Socioeconomic variables correlated with death (rural counties with a high proportion of elderly and young) differ from those related to property damage (rural counties with high percentage of Black, Hispanic and Native American populations below the poverty line). Results confirm that social vulnerability influences death and damage from floods in the USA. Model results indicate that social vulnerability models related to specific hazards and outcomes perform better than generic social vulnerability indices (e.g., SoVI) in predicting non-coastal flood death and damage. Hazard- and outcome-specific indices could be used to better direct efforts to ameliorate flood death and damage towards the people and places that need it most. Future validation studies should examine other flood outcomes, such as evacuation, migration and health, across scales. Full article

Multiple studies have been carried out on the correct estimation of the damages (direct tangible losses) associated with floods. However, the complex analysis and the multitude of variables conditioning the damage estimation, as well as the uncertainty in their estimation, make it difficult, even today, to reach one single, complete solution to this problem. In no case has the influence that the topographic relationship between the main floor of a residential building and the surrounding land have in the estimation of flood economic damage been analysed. To carry out this analysis, up to a total of 28 magnitude–damage functions (with different characteristics and application scales) were selected on which the effect of over-elevation and under-elevation of the main floor of the houses was simulated (at intervals of 20 cm, between −0.6 and +1 metre). According to each of the two trends, an overestimation or underestimation of flood damage was observed. This pattern was conditioned by the specific characteristics of each magnitude–damage function, meaning that the percentage of damage became asymptotic from a certain flow depth value. In a real scenario, the consideration of this variable (as opposed to its non-consideration) causes an average variation in the damage estimation around 30%. Based on these results, the analysed variable can be considered as (1) another main source of uncertainty in the correct estimation of flood damage, and (2) an essential variable to take into account in a flood damage analysis for the correct estimation of loss. Full article

The capability of a GPU-parallelized numerical scheme to perform accurate and fast simulations of surface runoff in watersheds, exploiting high-resolution digital elevation models (DEMs), was investigated. The numerical computations were carried out by using an explicit finite volume numerical scheme and adopting a recent type of grid called Block-Uniform Quadtree (BUQ), capable of exploiting the computational power of GPUs with negligible overhead. Moreover, stability and zero mass error were ensured, even in the presence of very shallow water depth, by introducing a proper reconstruction of conserved variables at cell interfaces, a specific formulation of the slope source term and an explicit discretization of the friction source term. The 2D shallow water model was tested against two different literature tests and a real event that recently occurred in Italy for which field data is available. The influence of the spatial resolution adopted in different portions of the domain was also investigated for the last test. The achieved low ratio of simulation to physical times, in some cases less than 1:20, opens new perspectives for flood management strategies. Based on the result of such models, emergency plans can be designed in order to achieve a significant reduction in the economic losses generated by flood events. Full article

In the basin of the Amur River in the Russian Far East, the influence of watershed areas covered by forests on the river basin has a complex nature, and no strict functional dependency has been established yet between these two factors. A study of the Amur River watershed in the current conditions, between 2000 and 2016 (climate, forest coverage, fires, and felling), has been conducted using the ground and satellite observations. The purpose of the study was to identify their influence on the river behaviour (flow, flooding, and levels of water). The study of hydrological regime of rivers was conducted in conjunction with the analysis of the dynamics of forest and burns areas over the synchronised periods of time. A special attention was given to the changing nature of the species composition of the forests (coniferous and deciduous forests separately) from 2000 to 2016, and climatic parameters over thirty years (atmospheric temperature, dew point, precipitation). New facts have been obtained, which provide an explanation of the reasons for predominant prolonged trends in the dynamics of the summer streamflow. In the view of the general tendency toward increased forest coverage combining all species of forest stand, the trend in the dynamics of the coniferous species areas is negative. Therefore, a conclusion can be made, that one of the major factors in the increase of the river flood flow (alongside the atmospheric precipitation), is deforestation of primary coniferous forests on the watershed areas, in contrast with the deciduous forests, where the trend is positive. Practicability of such conclusions can be justified, as different types of forests have different root systems, which mellow the ground and facilitate partial loss of the atmospheric precipitation and its transformation into the groundwater flow. Besides, coniferous forests attract more frequent and intensive fires, more subjected to felling, have longer regeneration period, and also, use larger volumes of ground waters for growing and functioning. Consequently, with their disappearance, an increase in streamflow should be expected. No changes in surface temperature and humidity of the forest cover in the watersheds during 1980-2016 despite global warming. Therefore, annual variability of forested areas of watersheds is greatly influenced by fires and felling. There are reasons to assume, that because of the tendency for decreasing areas of coniferous forests, the conditions contributing to the increases in rivers’ flood flow and flood risks during monsoon and frontal cyclonic rainfalls will remain. Full article

Losses due to floods have dramatically increased over the past decades, and losses of companies, comprising direct and indirect losses, have a large share of the total economic losses. Thus, there is an urgent need to gain more quantitative knowledge about flood losses, particularly losses caused by business interruption, in order to mitigate the economic loss of companies. However, business interruption caused by floods is rarely assessed because of a lack of sufficiently detailed data. A survey was undertaken to explore processes influencing business interruption, which collected information on 557 companies affected by the severe flood in June 2013 in Germany. Based on this data set, the study aims to assess the business interruption of directly affected companies by means of a Random Forests model. Variables that influence the duration and costs of business interruption were identified by the variable importance measures of Random Forests. Additionally, Random Forest-based models were developed and tested for their capacity to estimate business interruption duration and associated costs. The water level was found to be the most important variable influencing the duration of business interruption. Other important variables, relating to the estimation of business interruption duration, are the warning time, perceived danger of flood recurrence and inundation duration. In contrast, the amount of business interruption costs is strongly influenced by the size of the company, as assessed by the number of employees, emergency measures undertaken by the company and the fraction of customers within a 50 km radius. These results provide useful information and methods for companies to mitigate their losses from business interruption. However, the heterogeneity of companies is relatively high, and sector-specific analyses were not possible due to the small sample size. Therefore, further sector-specific analyses on the basis of more flood loss data of companies are recommended. Full article

Flood is a frequent natural hazard that has significant financial consequences for Australia. In Australia, physical losses caused by floods are commonly estimated by stage-damage functions. These methods usually consider only the depth of the water and the type of buildings at risk. However, flood damage is a complicated process, and it is dependent on a variety of factors which are rarely taken into account. This study explores the interaction, importance, and influence of water depth, flow velocity, water contamination, precautionary measures, emergency measures, flood experience, floor area, building value, building quality, and socioeconomic status. The study uses tree-based models (regression trees and bagging decision trees) and a dataset collected from 2012 to 2013 flood events in Queensland, which includes information on structural damages, impact parameters, and resistance variables. The tree-based approaches show water depth, floor area, precautionary measures, building value, and building quality to be important damage-influencing parameters. Furthermore, the performance of the tree-based models is validated and contrasted with the outcomes of a multi-parameter loss function (FLFA_rs) from Australia. The tree-based models are shown to be more accurate than the stage-damage function. Consequently, considering more parameters and taking advantage of tree-based models is recommended. The outcome is important for improving established Australian flood loss models and assisting decision-makers and insurance companies dealing with flood risk assessment. Full article