scholarly journals Flood4castRTF: A Real-Time Urban Flood Forecasting Model

2021 ◽  
Vol 13 (10) ◽  
pp. 5651
Author(s):  
Michel Craninx ◽  
Koen Hilgersom ◽  
Jef Dams ◽  
Guido Vaes ◽  
Thomas Danckaert ◽  
...  
Keyword(s):  
Climate Change ◽  
Real Time ◽  
Model Building ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Urban Flood ◽  
Flood Modelling ◽  
Physically Based ◽  
Physically Based Models ◽  
Modelling Approach

Worldwide, climate change increases the frequency and intensity of heavy rainstorms. The increasing severity of consequent floods has major socio-economic impacts, especially in urban environments. Urban flood modelling supports the assessment of these impacts, both in current climate conditions and for forecasted climate change scenarios. Over the past decade, model frameworks that allow flood modelling in real-time have been gaining widespread popularity. Flood4castRTF is a novel urban flood model that applies a grid-based approach at a modelling scale coarser than most recent detailed physically based models. Automatic model set-up based on commonly available GIS data facilitates quick model building in contrast with detailed physically based models. The coarser grid scale applied in Flood4castRTF pursues a better agreement with the resolution of the forcing rainfall data and allows speeding up of the calculations. The modelling approach conceptualises cell-to-cell interactions while at the same time maintaining relevant and interpretable physical descriptions of flow drivers and resistances. A case study comparison of Flood4castRTF results with flood results from two detailed models shows that detailed models do not necessarily outperform the accuracy of Flood4castRTF with flooded areas in-between the two detailed models. A successful model application for a high climate change scenario is demonstrated. The reduced data need, consisting mainly of widely available data, makes the presented modelling approach applicable in data scarce regions with no terrain inventories. Moreover, the method is cost effective for applications which do not require detailed physically based modelling.

scholarly journals Evaluation of the trophic status in a Mediterranean reservoir under climate change: An integrated modelling approach

2020 ◽  
Author(s):  
Carina Almeida ◽  
Paulo Branco ◽  
Pedro Segurado ◽  
Tiago B. Ramos ◽  
Teresa Ferreira ◽  
...  
Keyword(s):  
Climate Change ◽  
Nutrient Dynamics ◽  
Trophic Status ◽  
Integrated Modelling ◽  
Phosphorus Concentration ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Total Phosphorus Concentration ◽  
Southern Portugal ◽  
Modelling Approach

Abstract This study describes an integrated modelling approach to better understand the trophic status of the Montargil reservoir (southern Portugal) under climate change scenarios. The SWAT and CE-QUAL-W2 models were applied to the basin and reservoir, respectively, for simulating water and nutrient dynamics while considering one climatic scenario and two decadal timelines (2025–2034 and 2055–2064). Model simulations showed that the dissolved oxygen concentration in the reservoir's hypolimnion is expected to decrease by 60% in both decadal timelines, while the chlorophyll-a concentration in the reservoir's epiliminion is expected to increase by 25%. The total phosphorus concentration (TP) is predicted to increase in the water column surface by 63% and in the hypolimion by 90% during the 2030 timeline. These results are even more severe during the 2060 timeline. Under this climate change scenario, the reservoir showed an eutrophic state during 70–80% of both timelines. Even considering measures that involve decreases in 30 to 35% of water use, the eutrophic state is not expected to improve.

scholarly journals Climate change impacts the protective effect of forests: A case study in Switzerland

2021 ◽  
Author(s):  
Christine Moos ◽  
Antoine Guisan ◽  
Christophe F. Randin ◽  
Heike Lischke
Keyword(s):  
Climate Change ◽  
Protective Effect ◽  
Climate Warming ◽  
Swiss Alps ◽  
Present Species ◽  
Future Research ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Ground Truth Data

Abstract In steep terrain, forests play an important role as natural means of protection against natural hazards, such as rockfall. Due to climate warming, significant changes in the protection service of these forests have to be expected in future. Shifts of current to more drought adapted species may result in temporary or even irreversible losses in the risk reduction provided by these forests. In this study, we assessed how the protective effect against rockfall of a protection forest in the western part of the Valais in the Swiss Alps may change in future, by combining dynamic forest modelling with a quantitative risk analysis. Current and future forest development was modelled with the spatially explicit forest model TreeMig for a moderate (RCP4.5) and an extreme (RCP8.5) climate change scenario. The simulated forest scenarios were compared to ground-truth data from the current forest complex. We quantified the protective effect of the different forest scenarios based on the reduction of rockfall risk for people and infrastructure at the bottom of the slope. Rockfall risk was calculated on the basis of three-dimensional rockfall simulations. The forest simulations predicted a clear decrease in basal area of most of the currently present species in future. The forest turned into a Q. pubescens dominated forest, for both climate scenarios, and mixed with P. sylvestris in RCP4.5. F. sylvatica completely disappeared in RCP8.5. With climate warming, a clear increase in risk is expected for both climate change scenarios. In the long-term (> 100 years), a stabilization of risk, or even a slight decline may be expected due to an increase in biomass of the trees. The results of this study further indicate that regular forest interventions may promote regeneration and thus accelerate the shift in species distribution. Future research should address the long-term effect of different forest management strategies on the protection service of forests under climate change.

Improving Urban Flood Resilience under Climate Change Scenarios in a Tropical Watershed Using Low-Impact Development Practices

2021 ◽  
Vol 26 (12) ◽  
Author(s):  
Tiago Souza Mattos ◽  
Paulo Tarso S. Oliveira ◽  
Leonardo de Souza Bruno ◽  
Nilo Dinis de Oliveira ◽  
Jose G. Vasconcelos ◽  
...  
Keyword(s):  
Climate Change ◽  
Low Impact Development ◽  
Climate Change Scenarios ◽  
Urban Flood ◽  
Tropical Watershed

scholarly journals Future Runoff Analysis in the Mekong River Basin under a Climate Change Scenario Using Deep Learning

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1556 ◽  
Author(s):  
Daeeop Lee ◽  
Giha Lee ◽  
Seongwon Kim ◽  
Sungho Jung
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Change Scenario ◽  
Swat Model ◽  
Mekong River ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Rainfall Runoff ◽  
Runoff Prediction ◽  
Runoff Analysis

In establishing adequate climate change policies regarding water resource development and management, the most essential step is performing a rainfall-runoff analysis. To this end, although several physical models have been developed and tested in many studies, they require a complex grid-based parameterization that uses climate, topography, land-use, and geology data to simulate spatiotemporal runoff. Furthermore, physical rainfall-runoff models also suffer from uncertainty originating from insufficient data quality and quantity, unreliable parameters, and imperfect model structures. As an alternative, this study proposes a rainfall-runoff analysis system for the Kratie station on the Mekong River mainstream using the long short-term memory (LSTM) model, a data-based black-box method. Future runoff variations were simulated by applying a climate change scenario. To assess the applicability of the LSTM model, its result was compared with a runoff analysis using the Soil and Water Assessment Tool (SWAT) model. The following steps (dataset periods in parentheses) were carried out within the SWAT approach: parameter correction (2000–2005), verification (2006–2007), and prediction (2008–2100), while the LSTM model went through the process of training (1980–2005), verification (2006–2007), and prediction (2008–2100). Globally available data were fed into the algorithms, with the exception of the observed discharge and temperature data, which could not be acquired. The bias-corrected Representative Concentration Pathways (RCPs) 4.5 and 8.5 climate change scenarios were used to predict future runoff. When the reproducibility at the Kratie station for the verification period of the two models (2006–2007) was evaluated, the SWAT model showed a Nash–Sutcliffe efficiency (NSE) value of 0.84, while the LSTM model showed a higher accuracy, NSE = 0.99. The trend analysis result of the runoff prediction for the Kratie station over the 2008–2100 period did not show a statistically significant trend for neither scenario nor model. However, both models found that the annual mean flow rate in the RCP 8.5 scenario showed greater variability than in the RCP 4.5 scenario. These findings confirm that the LSTM runoff prediction presents a higher reproducibility than that of the SWAT model in simulating runoff variation according to time-series changes. Therefore, the LSTM model, which derives relatively accurate results with a small amount of data, is an effective approach to large-scale hydrologic modeling when only runoff time-series are available.

scholarly journals Using species distribution models to infer potential climate change-induced range shifts of freshwater fish in south-eastern Australia

2011 ◽  
Vol 62 (9) ◽  
pp. 1043 ◽  
Author(s):  
Nick Bond ◽  
Jim Thomson ◽  
Paul Reich ◽  
Janet Stein
Keyword(s):  
Climate Change ◽  
Freshwater Fish ◽  
Species Distribution ◽  
Climate Change Scenario ◽  
Species Distribution Models ◽  
Range Shifts ◽  
Future Climate Change ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Distribution Models

There are few quantitative predictions for the impacts of climate change on freshwater fish in Australia. We developed species distribution models (SDMs) linking historical fish distributions for 43 species from Victorian streams to a suite of hydro-climatic and catchment predictors, and applied these models to explore predicted range shifts under future climate-change scenarios. Here, we present summary results for the 43 species, together with a more detailed analysis for a subset of species with distinct distributions in relation to temperature and hydrology. Range shifts increased from the lower to upper climate-change scenarios, with most species predicted to undergo some degree of range shift. Changes in total occupancy ranged from –38% to +63% under the lower climate-change scenario to –47% to +182% under the upper climate-change scenario. We do, however, caution that range expansions are more putative than range contractions, because the effects of barriers, limited dispersal and potential life-history factors are likely to exclude some areas from being colonised. As well as potentially informing more mechanistic modelling approaches, quantitative predictions such as these should be seen as representing hypotheses to be tested and discussed, and should be valuable for informing long-term strategies to protect aquatic biota.

scholarly journals ADAPTATIONS ASSESSMENT ON THE IMPACTS OF FLOODING UNDER CURRENT CONDITION AND CLIMATE CHANGE SCENARIO, CASE STUDY: CENTINI VILLAGE, INDONESIA

2017 ◽  
Vol 19 (3) ◽  
pp. 163 ◽  
Author(s):  
Adjie Pamungkas ◽  
Sarah Bekessy ◽  
Ruth Lane
Keyword(s):  
Climate Change ◽  
Climate Change Scenario ◽  
Recovery Process ◽  
Future Climate Change ◽  
Small Scale ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Community Vulnerability ◽  
Vulnerability Model

Reducing community vulnerability to flooding is increasingly important given predicted intensive flood events in many parts of the world. We built a community vulnerability model to explore the effectiveness of a range of proactive and reactive adaptations to reduce community vulnerability to flood. The model consists of floods, victims, housings, responses, savings, expenditure and income sub models. We explore the robustness of adaptations under current conditions and under a range of future climate change scenarios. We present results of this model for a case study of Centini Village in Lamongan Municipality, Indonesia, which is highly vulnerable to the impacts of annual small-scale and infrequent extreme floods.  We compare 11 proactive adaptations using indicators of victims, damage/losses and recovery process to reflect the level of vulnerability. We find that reforestation and flood infrastructure redevelopment are the most effective proactive adaptations for minimising vulnerability to flood under current condition. Under climate change scenario, the floods are predicted to increase 17% on the average and 5% on the maximum measurements. The increasing floods result reforestation is the only effective adaptations in the future under climate change scenario.

scholarly journals Case for Climate Smart Agriculture in Addressing the Threat of Climate Change

2021 ◽  
pp. 131-145
Author(s):  
John Saviour Yaw Eleblu ◽  
Eugene Tenkorang Darko ◽  
Eric Yirenkyi Danquah
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Food Crop ◽  
Adverse Conditions ◽  
Climate Change And Variability ◽  
Food Crop Production ◽  
Smart Agriculture ◽  
Available Information

AbstractClimate smart agriculture (CSA) embodies a blend of innovations, practices, systems, and investment programmes that are used to mitigate against the adverse effects of climate change and variability on agriculture for sustained food production. Food crop production under various climate change scenarios requires the use of improved technologies that are called climate smart agriculture to ensure increased productivity under adverse conditions of increased global temperatures, frequent and more intense storms, floods and drought stresses. This chapter summarizes available information on climate change and climate smart agriculture technologies. It is important to evaluate each climate change scenario and provide technologies that farmers, research scientists, and policy drivers can use to create the desired climate smart agriculture given the array of tools and resources available.

scholarly journals Comparing model performance of two rainfall-runoff models in the Rhine basin using different atmospheric forcing data sets

2007 ◽  
Vol 4 (6) ◽  
pp. 4325-4360 ◽  
Author(s):  
A. H. te Linde ◽  
J. C. J. H. Aerts ◽  
R. T. W. L. Hurkmans ◽  
M. Eberle
Keyword(s):  
Climate Change ◽  
Model Performance ◽  
Change Scenario ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Meteorological Forcing ◽  
Lumped Model ◽  
Distributed Models ◽  
Rhine Basin ◽  
Physically Based

Abstract. Due to the growing wish and necessity to simulate the possible effects of climate change on the discharge regime on large rivers such as the Rhine in Europe, there is a need for well performing hydrological models that can be applied in climate change scenario studies. There exists large variety in available models and there is an ongoing debate in research on rainfall-runoff modelling on whether or not physically based distributed models better represent observed discharges than conceptual lumped model approaches do. In this paper, the hydrological models HBV and VIC were compared for the Rhine basin by testing their performance in simulating discharge. Overall, the semi-distributed conceptual HBV model performed much better than the distributed physically based VIC model (E=0.62, r2=0.65 vs. E=0.31, r2=0.54 at Lobith). It is argued here that even for a well-documented river basin such as the Rhine, more complex modelling does not automatically lead to better results. Moreover, it is concluded that meteorological forcing data has a considerable influence on model performance, irrespectively to the type of model structure and the need for ground-based meteorological measurements is emphasized.

scholarly journals Methods for the Design of Climate Change Scenario in Slovakia for the 21St Century

2009 ◽  
Vol 1 (1) ◽  
pp. 77-90 ◽  
Author(s):  
Marian Melo ◽  
Milan Lapin ◽  
Ingrid Damborska
Keyword(s):  
Climate Change ◽  
Time Series ◽  
21St Century ◽  
Climate Change Scenario ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Precipitation Time Series ◽  
Impact Studies ◽  
Temperature And Precipitation ◽  
Mean Temperature

Abstract In this paper methods of climate-change scenario projection in Slovakia for the 21st century are outlined. Temperature and precipitation time series of the Hurbanovo Observatory in 1871-2007 (Slovak Hydrometeorological Institute) and data from four global GCMs (GISS 1998, CGCM1, CGCM2, HadCM3) are utilized for the design of climate change scenarios. Selected results of different climate change scenarios (based on different methods) for the region of Slovakia (up to 2100) are presented. The increase in annual mean temperature is about 3°C, though the results are ambiguous in the case of precipitation. These scenarios are required by users in impact studies, mainly from the hydrology, agriculture and forestry sectors.

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