scholarly journals Assessment of the Impact of Climate Change on Daily Extreme Peak and Low Flows of Zenne Basin in Belgium

Hydrology ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 38 ◽  
Author(s):  
Olkeba Leta ◽  
Willy Bauwens
Keyword(s):  
Climate Change ◽  
Swat Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Agricultural Crop ◽  
Impact Of Climate Change ◽  
Low Flows ◽  
Hydrological Extremes ◽  
The Impact

Integrating hydrology with climate is essential for a better understanding of the impact of present and future climate on hydrological extremes, which may cause frequent flooding, drought, and shortage of water supply. This study assessed the impact of future climate change on the hydrological extremes (peak and low flows) of the Zenne river basin (Belgium). The objectives were to assess how climate change impacts basin-wide extreme flows and to provide a detailed overview of the impacts of four future climate change scenarios compared to the control (baseline) values. The scenarios are high (wet) summer (projects a future with high storm rain in summer), high (wet) winter (predicts a future with high rainfall in winter), mean (considers a future with intermediate climate conditions), and low (dry) (projects a future with low rainfall during winter and summer). These scenarios were projected by using the Climate Change Impact on HYDRological extremes perturbation tool (CCI-HYDR), which was (primarily) developed for Belgium to study climate change. We used the Soil and Water Assessment Tool (SWAT) model to predict the impact of climate change on hydrological extremes by the 2050s (2036–2065) and the 2080s (2066–2095) by perturbing the historical daily data of 1961–1990. We found that the four climate change scenarios show quite different impacts on extreme peak and low flows. The extreme peak flows are expected to increase by as much as 109% under the wet summer scenario, which could increase adverse effects, such as flooding and disturbance of the riverine ecosystem functioning of the river. On the other hand, the low (dry) scenario is projected to cause a significant decrease in both daily extreme peak and low flows, by as much as 169% when compared to the control values, which would cause problems, such as droughts, reduction in agricultural crop productivity, and increase in drinking water and other water use demands. More importantly, larger negative changes in low flows are predicted in the downstream part of the basin where a higher groundwater contribution is expected, indicating the sensitivity of a basin to the impact of climate change may vary spatially and depend on basin characteristic. Overall, an amplified, as well as an earlier, occurrence of hydrological droughts is expected towards the end of this century, suggesting that water resources managers, planners, and decision makers should prepare appropriate mitigation measures for climate change for the Zenne and similar basins.

Impact of climate change on streamflow and water quality in the upper Dong Nai river basin, Vietnam

2018 ◽  
pp. 70-79 ◽  
Author(s):  
Le Viet Thang ◽  
Dao Nguyen Khoi ◽  
Ho Long Phi
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
River Basin ◽  
Sediment Load ◽  
Swat Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Nutrient Load ◽  
Impact Of Climate Change ◽  
The Impact

In this study, we investigated the impact of climate change on streamflow and water quality (TSS, T-N, and T-P loads) in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a reasonable tool for simulating streamflow and water quality for this basin. Based on the well-calibrated SWAT model, the responses of streamflow, sediment load, and nutrient load to climate change were simulated. Climate change scenarios (RCP 4.5 and RCP 8.5) were developed from five GCM simulations (CanESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) using the delta change method. The results indicated that climate in the study area would become warmer and wetter in the future. Climate change leads to increases in streamflow, sediment load, T-N load, and T-P load. Besides that, the impacts of climate change would exacerbate serious problems related to water shortage in the dry season and soil erosion and degradation in the wet season. In addition, it is indicated that changes in sediment yield and nutrient load due to climate change are larger than the corresponding changes in streamflow.

Selection of models to describe the temperature-dependent development of Neoleucinodes elegantalis (Lepidoptera: Crambidae) and its application to predict the species voltinism under future climate conditions

2021 ◽  
pp. 1-9
Author(s):  
Hevellyn Talissa dos Santos ◽  
Cesar Augusto Marchioro
Keyword(s):  
Climate Change ◽  
Linear Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Dependent ◽  
Dependent Development ◽  
Degree Day ◽  
Non Linear ◽  
The Impact

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.

How to model the impact of climate change on vector-borne diseases?

2021 ◽  
pp. 26-31
Author(s):  
Cyril Caminade
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Mathematical Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Risk ◽  
Vector Borne Diseases ◽  
Impact Of Climate Change ◽  
Vector Borne ◽  
The Impact

Abstract This expert opinion provides an overview of mathematical models that have been used to assess the impact of climate change on ticks and tick-borne diseases, ways forward in terms of improving models for the recent context and broad guidelines for conducting future climate change risk assessment.

scholarly journals Future Climate Change Will Have a Positive Effect on Populus davidiana in China

Forests ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 1120 ◽  
Author(s):  
Jie Li ◽  
Guan Liu ◽  
Qi Lu ◽  
Yanru Zhang ◽  
Guoqing Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Human Disturbance ◽  
Vulnerability Index ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Degree Of Protection ◽  
Populus Davidiana ◽  
The Impact ◽  
Degree Of Fragmentation

Since climate change significantly affects global biodiversity, a reasonable assessment of the vulnerability of species in response to climate change is crucial for conservation. Most existing methods estimate the impact of climate change on the vulnerability of species by projecting the change of a species’ distribution range. This single-component evaluation ignores the impact of other components on vulnerability. In this study, Populus davidiana (David’s aspen), a tree species widely used in afforestation projects, was selected as the research subject under four future climate change scenarios (representative concentration pathway (RCP)2.6, RCP4.5, RCP6.0, and RCP8.5). Exposure components of range change as well as the degree of fragmentation, degree of human disturbance, and degree of protection were considered simultaneously. Then, a multicomponent vulnerability index was established to assess the effect of future climate change on the vulnerability of P. davidiana in China. The results show that the distribution range of P. davidiana will expand to the northwest of China under future climate change scenarios, which will lead to an increased degree of protection and a decreased degree of human disturbance, and hardly any change in the degree of fragmentation. The multicomponent vulnerability index values of P. davidiana under the four emission scenarios are all positive by 2070, ranging from 14.05 to 38.18, which fully indicates that future climate change will be conducive to the survival of P. davidiana. This study provides a reference for the development of conservation strategies for the species as well as a methodological case study for multicomponent assessment of species vulnerability to future climate change.

scholarly journals Projecting the impact of climate change on the transmission of Ross River virus: methodological challenges and research needs

2014 ◽  
Vol 142 (10) ◽  
pp. 2013-2023 ◽  
Author(s):  
W. YU ◽  
P. DALE ◽  
L. TURNER ◽  
S. TONG
Keyword(s):  
Climate Change ◽  
Environmental Factors ◽  
Socioeconomic Development ◽  
Future Climate Change ◽  
Ross River Virus ◽  
Climate Change Scenarios ◽  
Impact Of Climate Change ◽  
Development Scenarios ◽  
Methodological Challenges ◽  
The Impact

SUMMARYRoss River virus (RRV) is the most common vector-borne disease in Australia. It is vitally important to make appropriate projections on the future spread of RRV under various climate change scenarios because such information is essential for policy-makers to identify vulnerable communities and to better manage RRV epidemics. However, there are many methodological challenges in projecting the impact of climate change on the transmission of RRV disease. This study critically examined the methodological issues and proposed possible solutions. A literature search was conducted between January and October 2012, using the electronic databases Medline, Web of Science and PubMed. Nineteen relevant papers were identified. These studies demonstrate that key challenges for projecting future climate change on RRV disease include: (1) a complex ecology (e.g. many mosquito vectors, immunity, heterogeneous in both time and space); (2) unclear interactions between social and environmental factors; and (3) uncertainty in climate change modelling and socioeconomic development scenarios. Future risk assessments of climate change will ultimately need to better understand the ecology of RRV disease and to integrate climate change scenarios with local socioeconomic and environmental factors, in order to develop effective adaptation strategies to prevent or reduce RRV transmission.

scholarly journals Predicting the impact of future climate change on streamflow in the Ugam River watershed

GeoScape ◽  
2021 ◽  
Vol 15 (2) ◽  
pp. 159-172
Author(s):  
Umidkhon Uzbekov ◽  
Bakhtiyor Pulatov ◽  
Bokhir Alikhanov ◽  
Alim Pulatov
Keyword(s):  
Climate Change ◽  
Assessment Tool ◽  
Human Life ◽  
Swat Model ◽  
Coupled Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Negative Consequences ◽  
Water Users ◽  
The Impact

Abstract Climate change affects the environment and human life across the planet and it is expected that the negative consequences will be large, especially in developing countries, such as Uzbekistan. The objective of this study was to predict the impact of future climate change on the streamflow of Ugam watershed (Chirchik River Basin (CRB)) using the Soil and Water Assessment Tool (SWAT). The outputs of Coupled Model Intercomparison Project Phase 5 (CMIP5), in combination with Representative Concentration Pathway 8.5, were used as future climate records for the period 2019−2048. The SWAT model was calibrated and validated for the streamflow from Ugam watershed through using the observed daily flow data from 2007 to 2011. The calibrated SWAT model was used to simulate the impact of future climate change on streamflow in the Ugam River for 2019−2048. The results show that the stream discharge is expected to decrease by approximately 42% within thirty years, with a 1.4 °C increase in temperature and 286 mm decrease in precipitation. The peak point for the future period is 40.32 m3 /s in 2037 whereas the lowest discharge, predicted for 2048, accounts for 22.54 m3 /s. Our study enables to understand the impact of climate change on water resources in the Ugam river and to increase the adaptive capacity of water users and managers in the region.

scholarly journals Risk from extreme precipitation and climate change on New Zealand’s residential property

2021 ◽  
Author(s):  
◽  
Jacob Pastor Paz
Keyword(s):  
Climate Change ◽  
Regression Model ◽  
Extreme Precipitation ◽  
Claim Data ◽  
Future Climate ◽  
Future Climate Change ◽  
Residential Property ◽  
Climate Change Scenarios ◽  
Property Damage ◽  
The Impact

<p><b>Three manuscripts form the basis of this dissertation exploring the effect of extreme precipitation and climate change on residential property in New Zealand. The first manuscript investigates the public insurer’s expected future liabilities, given future climate projections. Specifically, it examines the effect of extreme precipitation on direct property damage associated with rainfall-induced landslides, storms and floods. This study applies a fixed-effects panel regression model using claim data linked to extreme precipitation data over 2000-2017 and future climate change scenarios until 2100. The results show that liabilities will increase more if future greenhouse gasses emissions are higher. At the aggregate level, the percent change between past and future liabilities ranges between an increase of 7 to 8% higher in the next 20 years, and an increase between 9 to 25% increase by the end of the century, depending on the greenhouse gases emissions scenario.</b></p> <p>The second manuscript examines the risk of property damage from landslides associated with extreme precipitation. The focus is on the Nelson region as it displays the highest number of claims and pay-outs relative to its population and residential stock asset, and two thirds of the pay-outs come from a single event. The focus is on this event. This research combines past insurance claim data with geographic and sociodemographic data to estimate probability of damage, which is then combined with property replacement values and damage-ratio information to calculate the expected loses and map the spatial distribution of risk. The study integrates into the risk estimates the impact of climate change on precipitation based on an ‘attribution’ study. The analysis shows that slope and social deprivation play a significant role in the probability of damage. Furthermore, higher expected losses are associated with higher property values. </p> <p>The third manuscript studies the current and future risk of property damage from floods associated with extreme precipitation and climate change. The focus is on the most expensive event on record. This study applies a logistic cross-sectional regression model that exploits spatial variation of rainfall intensity-duration-frequency (with and without the effect of climate change), while controlling for other factors that might make a property more or less likely to experience damage. The expected monetary losses are calculated by factoring in the likelihood of flood damage derived from the regression model, property replacement values, and property vulnerability (based on flood-depth fragility functions). The results show that highest losses are associated with lowest annual exceedance probabilities (AEPs), still, sizeable losses are associated with higher AEPs. In this case, the effect of climate change for different emissions scenarios is too small to cause an economically meaningful increase in risk levels in the next 80 years (2100).</p>

scholarly journals Coupling Remote Sensing and Hydrological Model for Evaluating the Impacts of Climate Change on Streamflow in Data-Scarce Environment

2021 ◽  
Vol 13 (24) ◽  
pp. 14025
Author(s):  
Fazlullah Akhtar ◽  
Usman Khalid Awan ◽  
Christian Borgemeister ◽  
Bernhard Tischbein
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Water Resources ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Climate Change Scenarios ◽  
Impact Of Climate Change ◽  
Streamflow Data ◽  
The Impact ◽  
Impacts Of Climate Change

The Kabul River Basin (KRB) in Afghanistan is densely inhabited and heterogenic. The basin’s water resources are limited, and climate change is anticipated to worsen this problem. Unfortunately, there is a scarcity of data to measure the impacts of climate change on the KRB’s current water resources. The objective of the current study is to introduce a methodology that couples remote sensing and the Soil and Water Assessment Tool (SWAT) for simulating the impact of climate change on the existing water resources of the KRB. Most of the biophysical parameters required for the SWAT model were derived from remote sensing-based algorithms. The SUFI-2 technique was used for calibrating and validating the SWAT model with streamflow data. The stream-gauge stations for monitoring the streamflow are not only sparse, but the streamflow data are also scarce and limited. Therefore, we selected only the stations that are properly being monitored. During the calibration period, the coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) were 0.75–0.86 and 0.62–0.81, respectively. During the validation period (2011–2013), the NSE and R2 values were 0.52–0.73 and 0.65–0.86, respectively. The validated SWAT model was then used to evaluate the potential impacts of climate change on streamflow. Regional Climate Model (RegCM4-4) was used to extract the data for the climate change scenarios (RCP 4.5 and 8.5) from the CORDEX domain. The results show that streamflow in most tributaries of the KRB would decrease by a maximum of 5% and 8.5% under the RCP 4.5 and 8.5 scenarios, respectively. However, streamflow for the Nawabad tributary would increase by 2.4% and 3.3% under the RCP 4.5 and 8.5 scenarios, respectively. To mitigate the impact of climate change on reduced/increased surface water availability, the SWAT model, when combined with remote sensing data, can be an effective tool to support the sustainable management and strategic planning of water resources. Furthermore, the methodological approach used in this study can be applied in any of the data-scarce regions around the world.

scholarly journals Are the effects of vegetation and soil changes as important as climate change impacts on hydrological processes?

2019 ◽  
Vol 23 (12) ◽  
pp. 4933-4954 ◽  
Author(s):  
Kabir Rasouli ◽  
John W. Pomeroy ◽  
Paul H. Whitfield
Keyword(s):  
Climate Change ◽  
Annual Runoff ◽  
Future Climate ◽  
Hydrological Processes ◽  
Future Climate Change ◽  
Impact Of Climate Change ◽  
Runoff Volume ◽  
Mountain Basins ◽  
The Impact ◽  
Soil Changes

Abstract. Hydrological processes are widely understood to be sensitive to changes in climate, but the effects of concomitant changes in vegetation and soils have seldom been considered in snow-dominated mountain basins. The response of mountain hydrology to vegetation/soil changes in the present and a future climate was modeled in three snowmelt-dominated mountain basins in the North American Cordillera. The models developed for each basin using the Cold Regions Hydrological Modeling platform employed current and expected changes to vegetation and soil parameters and were driven with recent and perturbed high-altitude meteorological observations. Monthly perturbations were calculated using the differences in outputs between the present- and a future-climate scenario from 11 regional climate models. In the three basins, future climate change alone decreased the modeled peak snow water equivalent (SWE) by 11 %–47 % and increased the modeled evapotranspiration by 14 %–20 %. However, including future changes in vegetation and soil for each basin changed or reversed these climate change outcomes. In Wolf Creek in the Yukon Territory, Canada, a statistically insignificant increase in SWE due to vegetation increase in the alpine zone was found to offset the statistically significant decrease in SWE due to climate change. In Marmot Creek in the Canadian Rockies, the increase in annual runoff due to the combined effect of soil and climate change was statistically significant, whereas their individual effects were not. In the relatively warmer Reynolds Mountain in Idaho, USA, vegetation change alone decreased the annual runoff volume by 8 %, but changes in soil, climate, or both did not affect runoff. At high elevations in Wolf and Marmot creeks, the model results indicated that vegetation/soil changes moderated the impact of climate change on peak SWE, the timing of peak SWE, evapotranspiration, and the annual runoff volume. However, at medium elevations, these changes intensified the impact of climate change, further decreasing peak SWE and sublimation. The hydrological impacts of changes in climate, vegetation, and soil in mountain environments were similar in magnitude but not consistent in direction for all biomes; in some combinations, this resulted in enhanced impacts at lower elevations and latitudes and moderated impacts at higher elevations and latitudes.

scholarly journals Risk from extreme precipitation and climate change on New Zealand’s residential property

2021 ◽  
Author(s):  
Jacob Pastor Paz
Keyword(s):  
Climate Change ◽  
Regression Model ◽  
Extreme Precipitation ◽  
Claim Data ◽  
Future Climate ◽  
Future Climate Change ◽  
Residential Property ◽  
Climate Change Scenarios ◽  
Property Damage ◽  
The Impact

<p><b>Three manuscripts form the basis of this dissertation exploring the effect of extreme precipitation and climate change on residential property in New Zealand. The first manuscript investigates the public insurer’s expected future liabilities, given future climate projections. Specifically, it examines the effect of extreme precipitation on direct property damage associated with rainfall-induced landslides, storms and floods. This study applies a fixed-effects panel regression model using claim data linked to extreme precipitation data over 2000-2017 and future climate change scenarios until 2100. The results show that liabilities will increase more if future greenhouse gasses emissions are higher. At the aggregate level, the percent change between past and future liabilities ranges between an increase of 7 to 8% higher in the next 20 years, and an increase between 9 to 25% increase by the end of the century, depending on the greenhouse gases emissions scenario.</b></p> <p>The second manuscript examines the risk of property damage from landslides associated with extreme precipitation. The focus is on the Nelson region as it displays the highest number of claims and pay-outs relative to its population and residential stock asset, and two thirds of the pay-outs come from a single event. The focus is on this event. This research combines past insurance claim data with geographic and sociodemographic data to estimate probability of damage, which is then combined with property replacement values and damage-ratio information to calculate the expected loses and map the spatial distribution of risk. The study integrates into the risk estimates the impact of climate change on precipitation based on an ‘attribution’ study. The analysis shows that slope and social deprivation play a significant role in the probability of damage. Furthermore, higher expected losses are associated with higher property values. </p> <p>The third manuscript studies the current and future risk of property damage from floods associated with extreme precipitation and climate change. The focus is on the most expensive event on record. This study applies a logistic cross-sectional regression model that exploits spatial variation of rainfall intensity-duration-frequency (with and without the effect of climate change), while controlling for other factors that might make a property more or less likely to experience damage. The expected monetary losses are calculated by factoring in the likelihood of flood damage derived from the regression model, property replacement values, and property vulnerability (based on flood-depth fragility functions). The results show that highest losses are associated with lowest annual exceedance probabilities (AEPs), still, sizeable losses are associated with higher AEPs. In this case, the effect of climate change for different emissions scenarios is too small to cause an economically meaningful increase in risk levels in the next 80 years (2100).</p>

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