Hydrological impact of widespread afforestation in Great Britain using a large ensemble of modelled scenarios

Ambitious afforestation proposals in the last decade target potential flood mitigation and carbon storage benefits but without a systematic, large-scale (>1000 km2) quantitative evaluation of their impacts on streamflow. Here, we assess the impact of afforestation on streamflow across twelve diverse catchments (c.500-10,000 km2) using a high-resolution land-surface model with a large ensemble of afforestation scenarios. Afforestation consistently decreases median and low streamflow. Median modelled flow is reduced by 2.8% ± 1.0 (1 s.d.), or 10 mm yr−1 ± 2.1 (1 s.d.), for a ten-percentage point increase in catchment broadleaf woodland. We find no nationally-consistent reduction of extreme floods. In larger catchments, planting extent is a stronger control on streamflow than location. Our results suggest that despite its potential environmental and societal benefits, widespread afforestation may inadvertently reduce water availability, particularly in drier areas, whilst only providing a modest reduction in extreme flood flows.

Cross-continental hydroclimate proxies: Tree-rings in Central Chile reconstruct historical streamflow in Southeastern South American rivers

Regional teleconnections permit cross-continental modeling of hydroclimate throughout the world. Tree-rings are a good hydroclimatic proxy used to reconstruct drought and streamflow in regions that respond to common global forcings. We used a multi-species dataset of 32 tree-ring width chronologies from Chile and Uruguay as a climate proxy to infer annual streamflow (Q) variability in the Negro River basin, a grassland-dominated watershed of lowland Southeastern South America. A positive linear correlation between tree-ring chronologies from Central Chile and annual Negro River instrumental streamflow from 1957 to 2012 indicated a cross-continental teleconnection between hydroclimate variability in Central Chile and Northeastern Uruguay. This relationship was mediated in part by the El Niño Southern Oscillation (ENSO), whereby the El Nino 3.4 Index was positively correlated with regional rainfall, annual tree growth, and Q anomalies. Despite the proximity of Uruguayan tree-ring chronologies to Negro River hydrometric stations, the Chilean tree-ring chronologies best predicted annual streamflow. Thus, using tree-ring data from four long-term moisture-sensitive chronologies of the species Cryptocarya alba in Central Chile (32–34°S), we present the first streamflow reconstruction (1890–2009) in the lower La Plata Basin. The reconstruction supports regional evidence for increasing frequency of extreme flood years over the past century in Uruguay. We demonstrate how climate teleconnections that mediate local hydroclimate variability permit the cross-continental reconstruction of streamflow, filling a major geographical gap in historical proxies for flooding and drought in grassland biomes of the southern hemisphere.

Nonstationary Bayesian Modeling of Extreme Flood Risk and Return Period Affected by Climate Variables for Xiangjiang River Basin, in South-Central China

The accurate design flood of hydraulic engineering is an important precondition to ensure the safety of residents, and the high precision estimation of flood frequency is a vital perquisite. The Xiangjiang River basin, which is the largest river in Hunan Province of China, is highly inclined to floods. This paper aims to investigate the annual maximum flood peak (AMFP) risk of Xiangjiang River basin under the climate context employing the Bayesian nonstationary time-varying moment models. Two climate covariates, i.e., the average June-July-August Artic Oscillation and sea level pressure in the Northwest Pacific Ocean, are selected and found to exhibit significant positive correlation with AMFP through a rigorous statistical analysis. The proposed models are tested with three cases, namely, stationary, linear-temporal and climate-based conditions. The results both indicate that the climate-informed model demonstrates the best performance as well as sufficiently explain the variability of extreme flood risk. The nonstationary return periods estimated by the expected number of exceedances method are larger than traditional ones built on the stationary assumption. In addition, the design flood could vary with the climate drivers which has great implication when applied in the context of climate change. This study suggests that nonstationary Bayesian modelling with climatic covariates could provide useful information for flood risk management.

Assessment of building damages and adaptation options under extreme flood scenarios in Shanghai

Plenty of various measures have been taken to mitigate flood losses in Shanghai over thousands of years, including the construction of sea dikes and floodwalls. However, the combined effects of intensified rainstorms, sea-level rise, land subsidence, and rapid urbanization are exacerbating extreme flood risks and potential flood losses in the fast-developing coastal city. In light of these changes, this article presents an assessment of possible exposure and damage losses of buildings in Shanghai (including residential, commercial, workplace, and industrial buildings). Based on extreme flood scenarios caused by storm surges, precipitation, and fluvial floods, current flood-defence standards will soon be overtaken. Further analyses show that the inundation area could reach 9 %, 16 %, 24 %, and 49 % of Shanghai (excluding the area of islands) under the 1/200, 1/500, 1/1000, and 1/5000-year flooding scenarios, respectively. This study finds, in terms of the total building damage, the 1/5000-year flood scenario damage is more than ten times the 1/200-year flood scenario. Accordingly, the average annual loss (AAL) of residential, commercial, office, and industrial buildings are 13.9, 2.3, 5.3, and 3.9 million USD. Specifically, among the 15 (non-island) districts in Shanghai, Pudong has the highest exposure and AAL at all the four flood scenarios, while the inner city (including seven districts) is also subject to extreme AAL of up to 40 % of its total building values. This study further addresses the possibilities of these extreme flood scenarios, and adaptation options such as: strategic urban planning, advanced building protections, and systematic flood management. Conclusions of the study provide information for scenario-based decision making and cost-benefit analysis for extreme flood risk management in Shanghai and is applicable to other similar coastal megacities.

Statistical Downscaling of Precipitation for Mahanadi Basin in India - Prediction of Future Streamflows

Climate change has long-term impacts on precipitation patterns, magnitude, and intensity, affecting regional water resources availability. Besides, understanding the interannual to decadal variations of streamflows in a river basin is paramount for watershed management, primarily extreme events such as floods and droughts. This study investigates impact of climate change in streamflows estimation for four sub-basins of the Mahanadi River, in India. The study includes three major components: (i) Historical trend analysis of hydroclimatic variables, using Mann-Kendall test; (ii) Statistical downscaling of GCM generated precipitation using change factor method and KnnCAD V4 stochastic weather generator; (iii) Dependable flow analysis of future streamflows predicted using Soil Water Assessment Tool (SWAT) model for various future GCM scenarios. It is observed that during the historical period, there is a decrease in number of rainy days and total annual precipitation in all sub-basins. However, the analysis also indicates an increase in flood intensity in two of the sub-basins. The decadal future precipitation has a marginal decrease in precipitation (up to 10%) for future scenarios; however, the precipitation events with high intensities increases. The results indicate that the magnitudes of 5% and 10% dependable flows are higher than the historically observed streamflows, for all future scenarios. This indicates a significant increase in extreme flood events in the basin. Further, only one of the sub-basins has shown an increase in water availability for agriculture and drinking water purposes (75% and 95% dependable flows) in the future. Understanding future flood events in the Mahanadi basin can help decision-makers to implement appropriate mitigation strategies.

Diamicton facies in the vicinity of Duhlata cave, Bosnek karst region, Southwestern Bulgaria

Karst caverns in the Upper Triassic dolostones of the Rusinovdel Formation are filled with allochthonous clastics (brecciaconglomerates with maximum boulder size) and locally with speleothems (flowstones). Deposition of the former (diamicton facies) by debris flows resulted from extreme flood events along the upper reaches of Struma river. The polymict material reflects erosion of various rock types in the source area but is dominated by resedimented Lower Triassic red beds. The diamictons are more or less similar to the few known examples from Quaternary karst caves.

The influence of climate change on discharge fluctuations in Slovenian rivers

In recent decades, an increase in the number of extreme flood events as well as extreme drought events has been observed in Slovenia. This rise the need for a comprehensive analysis of trends in discharge data series. In the study, statistical trends in seasonal and annual mean, maximum, extreme and low discharge values were investigated using the Mann Kendall test. The results show a temporal and spatial variability of trends in discharge. In general, a decreasing trend in water quantities in the rivers was observed. However, results at some gauging stations indicate statistically significant increasing trends, especially for maximum and extreme discharges. Additional analyses show that the discharge trends depend on the location of the gauging station.

Development of an Operational Framework for Flood Risk Management

Uncertainty is inherent to the decision-making process of flood risk management, and hence uncertainty management has been identified as crucial in the decision-making process. Flood management has been transformed towards flood risk management highlighting the stakeholder integration and adaptation to extreme flood events. Therefore, the development of multifunctional land uses over floodplains considering the multiple objectives of the stakeholders have become a key to manage uncertainty incorporated with flood risk management. Integration of multiple stakeholders in the decision-making process has been a challenging task. Therefore, spatial planning as a collaborative planning tool has become very important to manage flood risk. Operationalization of flood risk management is mainly governed by the characteristics of the planning processes and it is also coined with the governance context of each locality. However, the importance of the role of spatial planning in flood risk management is still hidden. Further, there is no common framework developed for structuring the complexity of the planning process. Therefore, this research attempts to develop a framework for the operationalization of flood risk management. The conceptual framework was developed based on a comprehensive literature review. Analytic Hierarchy Process (AHP) has been used and integrated with the Delphi technique to identify and calibrate the criteria and the sub-criteria of the framework. The developed framework has been validated with a case study. This research has been concluded that sixteen characteristics of the decision-making process contribute to the operationalization of flood risk management.