scholarly journals Assessment of the Water, Environmental, Economic and Social Vulnerability of a Watershed to the Potential Effects of Climate Change and Land Use Change

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1682
Author(s):  
Ismael Orozco ◽  
Adrián Martínez ◽  
Víctor Ortega
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Environmental Economic ◽  
Land Use Change ◽  
Arid Regions ◽  
Climate Models ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Distributed Hydrological Model ◽  
Semi Arid

In semi-arid regions, where hydrological resources are very vulnerable and where there are water shortages in many regions of the world, it is of great importance to assess the vulnerability that a system is facing or will face to the potential impacts of climatic changes and changes on the use of land. For that reason, this research focuses on evaluating the global vulnerability of a hydrological basin, taking into consideration these changes. Being different from the existing methodologies that assess the vulnerability, our methodology interconnects through a new interface a distributed hydrological model, global climate models, climate change scenarios, land use change scenarios and the largest number of system variables calculated with information from official sources. Another important point of our methodology is that it quantifies the global vulnerability of the system, taking into consideration hydrological, environmental, economic and social vulnerabilities. The results obtained show that the proposed methodology may provide a new approach to analyze vulnerability in semi-arid regions. Moreover, it made it possible to diagnose and establish that the greatest current and future vulnerabilities of the system are the result of activities in agricultural areas and urban centers.

scholarly journals Grassland production under global change scenarios for New Zealand pastoral agriculture

2014 ◽  
Vol 7 (3) ◽  
pp. 3307-3365
Author(s):  
E. D. Keller ◽  
W. T. Baisden ◽  
L. Timar ◽  
B. Mullan ◽  
A. Clark
Keyword(s):  
Climate Change ◽  
Land Use ◽  
New Zealand ◽  
Land Use Change ◽  
Global Climate Models ◽  
Model Parameters ◽  
High Fertility ◽  
Climate Change Scenarios ◽  
Pasture Production ◽  
N Cycle

Abstract. We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand (LURNZ) models to simulate pastoral agriculture and to make land-use change, intensification and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10% increase in New Zealand's national pasture production in 2020 under intensification and a 1–2% increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report (AR4) also show national increases of 1–2% in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4% under mild change but a decline of 1% under a more extreme case, whereas sheep/beef production declines in both cases by 3% and 13%, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first national-scale estimates using a model to evaluate the joint effects of climate change, CO2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasize that CO2 fertilisation and N cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of Decoupled Land-Use Change Scenarios (DLUCS): the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

scholarly journals Quantification of climate change and land cover/use transition impacts on runoff variations in the upper Hailar Basin, NE China

2020 ◽  
Vol 51 (5) ◽  
pp. 976-993
Author(s):  
Yuhui Yan ◽  
Baolin Xue ◽  
Yinglan A ◽  
Wenchao Sun ◽  
Hanwen Zhang
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Precipitation Change ◽  
Climate Change Scenarios ◽  
Reference Period ◽  
Ne China ◽  
Runoff Change ◽  
Hailar Basin ◽  
The Impact

Abstract Quantification of runoff change is vital for water resources management, especially in arid or semiarid areas. This study used the Soil and Water Assessment Tool (SWAT) distributed hydrological model to simulate runoff in the upper reaches of the Hailar Basin (NE China) and to analyze quantitatively the impacts of climate change and land-use change on runoff by setting different scenarios. Two periods, i.e., the reference period (before 1988) and the interference period (after 1988), were identified based on long-term runoff datasets. In comparison with the reference period, the contribution rates of both climate change and land-use change to runoff change in the Hailar Basin during the interference period were 83.58% and 16.42%, respectively. The simulation analysis of climate change scenarios with differential precipitation and temperature changes suggested that runoff changes are correlated positively with precipitation change and that the impact of precipitation change on runoff is stronger than that of temperature. Under different economic development scenarios adopted, land use was predicted to have a considerable impact on runoff. The expansion of forests within the basin might induce decreased runoff owing to enhanced evapotranspiration.

scholarly journals Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices

Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 639 ◽  
Author(s):  
Bright Freduah ◽  
Dilys MacCarthy ◽  
Myriam Adam ◽  
Mouhamed Ly ◽  
Alex Ruane ◽  
...  
Keyword(s):  
Climate Change ◽  
Arid Regions ◽  
Climate Models ◽  
Smallholder Farmers ◽  
Maize Yield ◽  
Climate Scenarios ◽  
Relative Standard ◽  
The Impact ◽  
Semi Arid ◽  
Smallholder Systems

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

Modelling the impacts of climate change and land-use change on the hydrology of Vietnam’s river basins

2020 ◽  
Author(s):  
Francesca Moschini ◽  
Iacopo Federico Ferrario ◽  
Barbara Hofmann
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Land Use Planning ◽  
Weighted Average ◽  
Surface Fluxes ◽  
Base Flow ◽  
Balance Model ◽  
Climate Change Scenarios ◽  
Hydrological Fluxes

<p>Quantifying how land-use change affects hydrological components is a challenge in hydrological science. It is not yet clear how changes in land use relate to runoff extremes and why some catchments are more sensitive to land-use change than others. Identifying which areas are hydrologically more sensitive to land-use change can lead to better land-use planning, reduction of the impacts of extreme rainfall events and extended dry periods. In this study we aim to quantify how land-use change and climate change are affecting the hydrological response of  Vietnam’s basins. Over the past decades the country’s land use has shifted from forest to agriculture, with very high production of rice, coffee, tea, pepper and sugar cane.</p><p>We combine the historical, the Intergovernmental Panel on Climate Change’s (IPCC) Representative Concentration Pathway (RCP) RCP4.5 and RCP8.5 climate change scenarios developed for Vietnam, with two different land cover maps (from the years 1992 and 2017). The combined and separate effect of land use and climate change are assessed and the most sensitive to change areas are identified. The Variable infiltration Capacity (VIC) surface water and energy balance model applied here is a grid-based model that calculates evapotranspiration, runoff, base flow, soil moisture and other hydrological fluxes. Surface heterogeneity within VIC is represented by a tiled approach, whereby the surface of each grid-box comprises fractions of the different surface types. For each surface type of the grid-box, the energy and water balances are solved, and a weighted average is calculated from the individual surface fluxes for each grid-box. Hydrological fluxes were compared for each grid cell and basin to analyse the degree of difference between the scenarios.</p><p>Significant changes in future hydrologic fluxes arise under both climate change scenarios pointing towards a severe increase in hydrological extremes. The changes in all the examined hydrological components are greater in the combined land-use and climate change experiments.</p>

The challenge of combining initialised and uninitialised decadal projections

2020 ◽  
Author(s):  
James Murphy
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Internal Climate Variability ◽  
Climate Risks ◽  
Early Results ◽  
Ensemble Mean ◽  
Decadal Climate

<p>The challenge of combining initialised and uninitialised decadal projections</p><p>James Murphy, Robin Clark, Nick Dunstone, Glen Harris, Leon Hermanson and Doug Smith</p><p>During the past 10 years or so, exploratory work in initialised decadal climate prediction, using global climate models started from recent analyses of observations, has grown into a coordinated international programme that contributes to IPCC assessments. At the same time, countries have continued to develop and update their national climate change scenarios.  These typically cover the full 21<sup>st</sup> century, including the initial decade that overlaps with the latest initialised forecasts. To date, however, national scenarios continue to be based exclusively on long-term (uninitialised) climate change simulations, with initialised information regarded as a separate stream of information.</p><p>We will use early results from the latest UK national scenarios (UKCP), and the latest CMIP6 initialised predictions, to illustrate the potential and challenges associated with the notion of combining both streams of information. This involves assessing the effects of initialisation on predictability and uncertainty (as indicated, for example, by the skill of ensemble-mean forecasts and the spread amongst constituent ensemble members). Here, a particular challenge involves interpretation of the “signal-to-noise” problem, in which ensemble-mean skill can sometimes be found which is larger than would be expected on the basis of the ensemble spread. In addition to initialisation, we will also emphasise the importance of understanding how the assessment of climate risks depends on other features of prediction system design, including the sampling of model uncertainties and the simulation of internal climate variability.</p>

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