A Framework to Develop Nationwide Flooding Extents Using Climate Models and Assess Forecast Potential for Flood Resilience

The methods used to simulate flood inundation extents can be significantly improved by high‐resolution spatial data captured over a large area. This paper presents a hydraulic analysis methodology and framework to estimate national‐level floodplain changes likely to be generated by climate change. The hydraulic analysis was performed using existing published Federal Emergency Management Agency 100‐year floodplains and estimated 100‐ and 10‐year return period peak flow discharges. The discharges were estimated using climate variables from global climate models for two future growth scenarios: Representative Concentration Pathways 2.6 and 8.5. River channel dimensions were developed based on existing regional United States Geological Survey publications relating bankfull discharges with channel characteristics. Mathematic relationships for channel bankfull topwidth, depth, and side slope to contributing drainage area measured at model cross sections were developed. The proposed framework can be utilized at a national level to identify critical areas for flood risk assessment. Existing hydraulic models at these “hot spots” could be repurposed for near–real‐time flood forecasting operations. Revitalizing these models for use in simulating flood scenarios in near–real time through the use of meteorological forecasts could provide useful information for first responders of flood emergencies.     

Analysis of Extreme Summer Rainfall Using Climate Teleconnections and Typhoon Characteristics in South Korea1

Abstract: It is now widely acknowledged that climate variability modulates the frequency of extreme hydrological events. Traditional methodologies for hydrologic frequency analysis are not devised to account for variation in the exogenous teleconnections. Flood frequency analysis is further plagued by the assumptions of stationary in the causal structure as well as ergodicity. Here, we propose a dynamical hierarchical Bayesian analysis to account for exogenous forcing that govern the summer season rainfall. The precursors for Korean summer rainfall at different frequencies are identified utilizing wavelet and independent component analyses. The sea surface temperatures, the ensemble of rainfall predictions by General Circulation Model, in addition to the typhoon attributes were found to have direct correlation with extreme rainfall events and were used as inputs to the logistic regression model. The model parameters are estimated using Markov Chain Monte Carlo and the resulting posterior distributions associated with individual inputs are analyzed to advance our understanding of the spatiotemporal impact of the teleconnections. Eight rainfall stations throughout Korea are considered in this analysis. We demonstrate that the probability of occurrence of extreme events could be successfully projected at a 90% rate of correct classification of extreme events.     

Rainfall timing and poultry litter application rate effects on phosphorus loss in surface runoff

Phosphorus (P) in runoff from pastures amended with poultry litter may be a significant contributor to eutrophication of lakes and streams in Georgia and other areas in the southeastern United States. The objectives of this research were to determine the effects of litter application rate and initial runoff timing on the long-term loss of P in runoff from surface-applied poultry litter and to develop equations that predict P loss in runoff under these conditions. Litter application rates of 2, 7, and 13 Mg ha(-1), and three rainfall scenarios applied to 1- x 2-m plots in a 3 x 3 randomized complete block design with three replications. The rainfall scenarios included (i) sufficient rainfall to produce runoff immediately after litter application; (ii) no rainfall for 30 d after litter application; and (iii) small rainfall events every 7 d (5 min at 75 mm h(-1)) for 30 d. Phosphorus loss was greatest from the high litter rate and immediate runoff treatments. Nonlinear regression equations based on the small plot study produced fairly accurate (r(2) = 0.52-0.62) prediction of P concentrations in runoff water from larger (0.75 ha) fields over a 2-yr period. Predicted P concentrations were closest to observed values for events that occurred shortly after litter application, and the relative error in predictions increased with time after litter application. In addition, previously developed equations relating soil test P levels to runoff P concentrations were ineffective in the presence of surface-applied litter.     

SPACE-TIME VALIDATION OF A THUNDERSTORM RAINFALL MODEL1

A probability model for predicting the occurrence and magnitude of thunderstorm rainfall developed in the southwestern United States was tested in the metropolitan Chicago area with reasonable success, especially for the moderate to the extreme runoff-producing events. The model requires the estimation of two parameters, the mean number of events per year and the conditional probability of rain given that an event has occurred. To tie in the data from more than one gage in an area, an event can be defined in several ways, such as the areal mean rainfall exceeding 0.50 inch and at least one gage receiving more than 1.0 inch. This type of definition allows both of the model parameters to be obtained from daily warm-season rainfall records. Regardless of the definition used a Poisson distribution adequately described the number of events per season. A negative binomial distribution was derived as representing the frequency density function for rainfall where several gages are employed in defining a storm. Chicago data fit both distributions very well at events with relatively high return periods. The results indicate the possibility of using the model on a regional basis where limited amount of data may be used to estimate parameters for extensive areas.     

Streamflow Responses to Climate Change: Analysis of Hydrologic Indicators in a New York City Water Supply Watershed

Recent works have indicated that climate change in the northeastern United States is already being observed in the form of shorter winters, higher annual average air temperature, and more frequent extreme heat and precipitation events. These changes could have profound effects on aquatic ecosystems, and the implications of such changes are less understood. The objective of this study was to examine how future changes in precipitation and temperature translate into changes in streamflow using a physically based semidistributed model, and subsequently how changes in streamflow could potentially impact stream ecology. Streamflow parameters were examined in a New York City water supply watershed for changes from model‐simulated baseline conditions to future climate scenarios (2081‐2100) for ecologically relevant factors of streamflow using the Indicators of Hydrologic Alterations tool. Results indicate that earlier snowmelt and reduced snowpack advance the timing and increase the magnitude of discharge in the winter and early spring (November‐March) and greatly decrease monthly streamflow later in the spring in April. Both the rise and fall rates of the hydrograph will increase resulting in increased flashiness and flow reversals primarily due to increased pulses during winter seasons. These shifts in timing of peak flows, changes in seasonal flow regimes, and changes in the magnitudes of low flow can all influence aquatic organisms and have the potential to impact stream ecology.     

气候变化视角下的污染场地绿色可持续修复新方向

全球气候变化背景下,绿色可持续修复已成为修复领域的必然趋势。极端天气频发和水文条件改变等气候变化会影响污染场地修复工程实施和修复技术适用性等,绿色可持续修复亟待进一步发展和完善。弹性修复是在绿色可持续修复的基础上,进一步应对和适应气候变化的新兴修复方向。英美等发达国家已经初步发展了弹性修复的理论和实践,本文通过探究污染场地修复与气候变化的交互作用,借鉴发达国家的相关经验和实践案例,为我国污染场地绿色可持续修复适应气候变化提出发展建议。     

ASSESSMENT OF POSSIBLE IMPACTS OF CLIMATE CHANGE IN AN URBAN CATCHMENT1

ABSTRACT: Stationarity of rainfall statistical parameters is a fundamental assumption in hydraulic infrastructure design that may not be valid in an era of changing climate. This study develops a framework for examining the potential impacts of future increases in short duration rainfall intensity on urban infrastructure and natural ecosystems of small watersheds and demonstrates this approach for the Mission/Wagg Creek watershed in British Columbia, Canada. Nonstationarities in rainfall records are first analyzed with linear regression analysis, and the detected trends are extrapolated to build potential future rainfall scenarios. The Storm Water Management Model (SWMM) is used to analyze the effects of increased rainfall intensity on design peak flows and to assess future drainage infrastructure capacity according to the derived scenarios. While the framework provided herein may be modified for cases in which more complex distributions for rainfall intensity are needed and more sophisticated stormwater management models are available, linear regressions and SWMM are commonly used in practice and are applicable for the Mission/Wagg Creek watershed. Potential future impacts on stream health are assessed using methods based on equivalent total impervious area. In terms of impacts on the drainage infrastructure, the results of this study indicate that increases in short duration rainfall intensity may be expected in the future but that they would not create severe impacts in the Mission/Wagg Creek system. The equivalent levels of imperviousness, however, suggest that the impacts on stream health could be far more damaging.     

Impacts of Climate Change on Extreme Precipitation Events Over Flamingo Tropicana Watershed1

Abstract: Climate change, particularly the projected changes to precipitation patterns, is likely to affect runoff both regionally and temporally. Extreme rainfall events are expected to become more intense in the future in arid urban areas and this will likely lead to higher streamflow. Through hydrological modeling, this article simulates an urban basin response to the most intense storm under anthropogenic climate change conditions. This study performs an event‐based simulation for shorter duration storms in the Flamingo Tropicana (FT) watershed in Las Vegas, Nevada. An extreme storm, defined as a 100‐year return period storm, is selected from historical records and perturbed to future climatic conditions with respect to multimodel multiscenario (A1B, A2, B1) bias corrected and spatially disaggregated data from the World Climate Research Programme's (WCRP's) database. The cumulative annual precipitation for each 30‐year period shows a continuous decrease from 2011 to 2099; however, the summer convective storms, which are considered as extreme storms for the study area, are expected to be more intense in future. Extreme storm events show larger changes in streamflow under different climate scenarios and time periods. The simulated peak streamflow and total runoff volume shows an increase from 40% to more than 150% (during 2041‐2099) for different climate scenarios. This type of analysis can help evaluate the vulnerability of existing flood control system and flood control policies.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Climate Change Impacts on Local Flood Risks in the U.S. Northeast: A Case Study on the Connecticut and Merrimack River Basins

This study investigates the potential impacts of climate change on future flows in the main stem of the Connecticut and Merrimack rivers within Massachusetts. The study applies two common climate projections based on (Representative Concentration Pathways), RCP 4.5 and RCP 8.5 and downscaled gridded climate projections from 14 global climate models (GCMs) to estimate the 100‐year, 24‐h extreme precipitation events for two future time‐periods: near‐term (2021–2060) and far‐term (2060–2099). 100‐year 24‐h precipitation events at near‐ and far‐term are compared to GCM‐driven historical extreme precipitation events during a base period (1960–1999) and results for RCP 8.5 scenario show average increases between 25%–50% during the near‐term compared to the base period and increases of over 50% during the far‐term. Streamflow conditions are generated with a distributed hydrological model where downscaled climate projections are used as inputs. For the near‐term, the medians of the GCMs using the RCP 4.5 and RCP 8.5 suggest 2.9%–8.1% increases in the 100‐year, 24‐h flow event in the Connecticut and an increase of 9.9%–13.7% in the Merrimack River. For the far‐term, the medians of the GCMs using the RCP 4.5 and RCP 8.5 suggest a 9.0%–14.1% increase in the Connecticut and 15.8%–20.6% for the Merrimack River. Ultimately, the results presented here can be used as a guidance for the long‐term management of infrastructures on the Connecticut and Merrimack River floodplains.     

Planning for cooler cities: a plan quality evaluation for Urban Heat Island consideration

ABSTRACT

City strategic plans and enabling policies provide a framework for and inform future development across multiple scales. An exemplar city strategic plan will be one based on evidence, enabled by complementary policy outcomes, and built on the knowledge of the existing landscape. This study evaluated the plan quality of eighteen metropolitan strategic plans for city members in the 100 Resilient Cities initiative. A protocol was developed containing thirty-two indicators to assess plans capacity to act as a strategic planning tool to develop, analyse and implement strategies for the Urban Heat Island (UHI) and climate change mitigation and adaptation. The evaluation indicated that strategies addressing the UHI are rarely included in metropolitan plans. Strategic plans showed a lack of evidence-base to inform the potential actions. Urban warming is often linked to extreme weather events anticipated under climate change, not the UHI as a systemic and increasing phenomenon. We recommend that the pathway to addressing UHI mitigation and adaptation may lie in its nexus to aspects of climate change that concurrently can serve to support liveable and resilient cities.     

FLOOD FREQUENCY ANALYSIS FOR SMALL WATERSHEDS IN SOUTHERN ILLINOIS1

ABSTRACT: Twenty-two gaging stations were selected for developing a regional flood frequency curve for small (area less than 2 square miles) watersheds in southern Illinois. Five probability functions were compared, and the extreme value type I function was selected to develop the regional flood curve. The curve was generated with the index flood method and also another empirical method that related the function parameters to the watershed area. Estimated peak discharges with various return periods were compared with the results obtained from multiple regression analysis.     

Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

应对气候变化治理模式国别比较分析

应对气候变化是全球各国共同面临的严峻挑战,而不同国家由于其自身发展阶段、治理水平等存在差异,气候治理模式也呈现不同特征。本文系统梳理了英国、德国、法国、美国、欧盟、日本、韩国、印度、巴西、南非等全球主要经济体和排放体的气候政策体系与机构设置情况,将其气候治理模式分为五类：政策引领型、法律缺失型、整体完备型、部分行业先行型和政策协调双缺失型,并从政治体制和党派态度、资源禀赋和强势部门、战略定位与气候叙事、公众态度与国际事件四个维度进行了影响因素的分析。建议我国未来可在加快推进气候立法、充分发挥制度优势、形成中国特色治理方案、推动建立公平合理互利共赢国际治理体系、落实完善“1+N”政策体系等方面加强工作部署,提升应对气候变化治理水平,促进“双碳”目标尽早实现。     

CLIMATE FACTOR FOR SMALL-BASIN FLOOD FREQUENCY1

ABSTRACT: A climate factor, C_T, (T = 2–, 25-, and 100-year recurrence intervals) that delineates regional trends in small-basin flood frequency was derived using data from 71 long-term rainfall record sites. Values of C_T at these sites were developed by a regression analysis that related rainfall-runoff model estimates of T-year floods to a sample set of 50 model calibrations. C_T was regionalized via kriging to develop maps depicting its geographic variation for a large part of the United States east of the 105th meridian. Kriged estimates of C_T and basin-runoff characteristics were used to compute regionalized T-year floods for 200 small drainage basins. Observed T-year flood estimates also were developed for these sites. Regionalized floods are shown to account for a large percentage of the variability in observed flood estimates with coefficients of determination ranging from 0.89 for 2-year floods to 0.82 for 100-year floods. The relative importance of the factors comprising regionalized flood estimates is evaluated in terms of scale (size of drainage area), basin-runoff characteristics (rainfall. runoff model parameters), and climate (C_T).     

From climate change impacts to adaptation: A development perspective for India

India has good reasons to be concerned about climate change as it could adversely affect the achievement of vital national development goals related to socio‐economic development, human welfare, health, energy availability and use, and infrastructure. The paper attempts to develop a framework for integrated impact assessment and adaptation responses, using a recently built railroad coastal infrastructure asset in India as an example. The framework links climate change variables — temperature, rainfall, sea level rise, extreme events, and other secondary variables — and sustainable development variables — technology, institutions, economic, and other policies. The study indicates that sustainable development variables generally reduce the adverse impacts on the system due to climate change alone, except when they are inadequately applied. The paper concludes that development is a vital variable for integrated impact assessment. Well crafted developmental policies could result in a less‐GHG intensive future, enhanced adaptive capacities of communities and systems, and lower impacts due to climate change.     

Method for Rapidly Assessing the Overtopping Risk of Bridges Due to Flooding over a Large Geographic Region

Hydraulic events are a leading cause of bridge failures. While these hydraulic events are accounted for in bridge design, changing environmental and land use conditions require continual updating of this risk. For example, after a bridge has been constructed, streamflow can change in unanticipated ways as a result of land use changes, geomorphic changes, and climate change. The objective of this research was to create a screening method able to quickly and inexpensively estimate overtopping risk across a collection of bridges based on the current streamflow conditions. The method uses a geographic information system, nationally available and standardized datasets, and recent regression equations to quantify bridge vulnerability to overtopping for flooding with varying return periods. This screening method could also be used to assist decision makers in updating the Waterway Adequacy field in the National Bridge Inventory, which indicates the overtopping risk of bridges. The method was applied to a portion of the Hampton Roads region of Virginia, United States that includes 475 bridges. The results of the analysis, when combined with transportation data for bridges, aid decision makers to assign further resources to complete more detailed analyses of bridges identified as being at risk for overtopping.     

Nonstationarity: Flood Magnification and Recurrence Reduction Factors in the United States1

Vogel, Richard M., Chad Yaindl, and Meghan Walter, 2011. Nonstationarity: Flood Magnification and Recurrence Reduction Factors in the United States. Journal of the American Water Resources Association (JAWRA) 47(3):464‐474. DOI: 10.1111/j.1752‐1688.2011.00541.x Abstract: It may no longer be reasonable to model streamflow as a stationary process, yet nearly all existing water resource planning methods assume that historical streamflows will remain unchanged in the future. In the few instances when trends in extreme events have been considered, most recent work has focused on the influence of climate change, alone. This study takes a different approach by exploring trends in floods in watersheds which are subject to a very broad range of anthropogenic influences, not limited to climate change. A simple statistical model is developed which can both mimic observed flood trends as well as the frequency of floods in a nonstationary world. This model is used to explore a range of flood planning issues in a nonstationary world. A decadal flood magnification factor is defined as the ratio of the T‐year flood in a decade to the T‐year flood today. Using historical flood data across the United States we obtain flood magnification factors in excess of 2‐5 for many regions of the United States, particularly those regions with higher population densities. Similarly, we compute recurrence reduction factors which indicate that what is now considered the 100‐year flood, may become much more common in many watersheds. Nonstationarity in floods can result from a variety of anthropogenic processes including changes in land use, climate, and water use, with likely interactions among those processes making it very difficult to attribute trends to a particular cause.     

Development of an Earthen Dam Break Database

Earthen embankment dams comprise 85% of all major operational dams in the United States. Assessment of peak flow rates for these earthen dams and the impacts on dam failure are of high interest to engineers and planners. Regression analysis is a frequently used risk assessment approach for earthen dams. In this paper, we present a decision support tool for assessing the applicability of nine regression equations commonly used by practitioners. Using data from 108 case studies, six parameters were observed to be significant factors predicting for peak flow as a metric for risk analysis. We present our work on an expanded earthen dam break database that relates the regression equations and underlying data. A web application, regression selection tool, is also presented to assess the appropriateness of a given model for a given test point. This graphical display allows users to visualize how their data point compares with the data used for the regression equation. These contributions improve estimates and better inform decision makers regarding operational and safety decisions.     

Projected Changes in Discharge in an Agricultural Watershed in Iowa

Our improved capability to adapt to the future changes in discharge is linked to our capability to predict the magnitude or at least the direction of these changes. For the agricultural United States Midwest, too much or too little water has severe socioeconomic impacts. Here, we focus on the Raccoon River at Van Meter, Iowa, and use a statistical approach to examine projected changes in discharge. We build on statistical models using rainfall and harvested corn and soybean acreage to explain the observed discharge variability. We then use projections of these two predictors to examine the projected discharge response. Results are based on seven global climate models part of the Coupled Model Intercomparison Project Phase 5 and two representative concentration pathways (RCPs 4.5 and 8.5). There is not a strong signal of change in the discharge projections under the RCP 4.5. However, the results for the RCP 8.5 point to a stronger changing signal related to larger projected increases in rainfall, resulting in increased trends, in particular, in the upper part of the discharge distribution (i.e., 60th percentile and above). Examination of two hypothetical agricultural scenarios indicates that these increasing trends could be alleviated by decreasing the extent of the agricultural production. We also discuss how the methodology presented in this study represents a viable approach to move forward with the concept of return period for engineering design and management in a nonstationary world.