Explore the vast range of titles available.

The impact of air temperature rise is eminent for the large deep lakes in the Italian subalpine district, climate change being caused there by both natural phenomena and anthropogenic greenhouse-gases (GHG) emissions. These oligomictic lakes are experiencing a decrease in the frequency of winter full turnover and an intensification of stability. As a result, hypolimnetic oxygen concentrations are decreasing and nutrients are accumulating in bottom water, with effects on the whole ecosystem functioning. Forecasting the future evolution of the mixing pattern is relevant to assess if a reduction in GHG releases would be able to revert such processes. The study focuses on Lake Maggiore, for which the thermal structure evolution under climate change in the 2016–2085 period was assessed through numerical simulations, performed with the General Lake Model (GLM). Different prospects of regional air temperature rise were considered, given by the Swiss Climate Change Scenarios CH2011. Multiple realisations were performed for each scenario to obtain robust statistical predictions, adopting random series of meteorological data produced with the Vector-Autoregressive Weather Generator (VG). Results show that a reversion in the increasing thermal stability would be possible only if global GHG emissions started to be reduced by ~ 2020, allowing an equilibrium mixing regime to be restored by the end of the twenty-first century. Otherwise, persistent lack of complete-mixing, severe water warming and extensive effects on water quality are to be expected for the centuries to come. These projections can be extended to the other lakes in the subalpine district.

Abstract This paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called “Data Assimilation Informed model Structure Improvement” (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes.

Castanea henryi, with edible nuts and timber value, is a key tree species playing essential roles in China's subtropical forest ecosystems. However, natural and human perturbations have nearly depleted its wild populations. The study identified the dominant environmental variables enabling and limiting its distribution and predicted its suitable habitats and distribution. The 212 occurrence records covering the whole distribution range of C. henryi in China and nine main bioclimatic variables were selected for detailed analysis. We applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate‐change scenarios. The limiting factors for distribution were accessed by Jackknife, percent contribution, and permutation importance. We found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces. The modeling results indicated temperature as the critical determinant of distribution patterns, including mean temperature of the coldest quarter, isothermality, and mean diurnal range. Winter low temperature imposed an effective constraint on its spread. Moisture served as a secondary factor in species distribution, involving precipitation seasonality and annual precipitation. Under future climate‐change scenarios, excellent habitats would expand and shift northwards, whereas range contraction would occur on the southern edge. Extreme climate change could bring notable range shrinkage. This study provided a basis for protecting the species' germplasm resources. The findings could guide the management, cultivation, and conservation of C. henryi, assisted by a proposed three‐domain operation framework: preservation areas, loss areas, and new areas, each to be implemented using tailor‐made strategies. Determined present suitable habitat conditions for Castanea henryi in China; Modeled the species' potential distribution under future climate‐change scenarios; Potential suitable habitats shifted northwards under moderate climate change.

Wetlands are an important natural source of methane (CH4), so it is important to quantify how their emissions may vary under future climate change conditions. The Qinghai–Tibet Plateau contains more than a third of China’s wetlands. Here, we simulated temporal and spatial variation in CH4 emissions from natural wetlands on the Qinghai–Tibet Plateau from 2008 to 2100 under Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Based on the simulation results of the TRIPLEX-GHG model forced with data from 24 CMIP5 models of global climate, we predict that, assuming no change in wetland distribution on the Plateau, CH4 emissions from natural wetlands will increase by 35%, 98% and 267%, respectively, under RCP 2.6, 4.5 and 8.5. The predicted increase in atmospheric CO2 concentration will contribute 10–28% to the increased CH4 emissions from wetlands on the Plateau by 2100. Emissions are predicted to be majorly in the range of 0 to 30.5 g C m−2·a−1 across the Plateau and higher from wetlands in the southern region of the Plateau than from wetlands in central or northern regions. Under RCP8.5, the methane emissions of natural wetlands on the Qinghai–Tibet Plateau increased much more significantly than that under RCP2.6 and RCP4.5.

We examined the vulnerability of 34 species of oaks (Quercus) and pines (Pinus) to the effects of global climate change in Mexico. We regionalized the HadCM2 model of climate change with local climatic data (mean annual temperature and rainfall) and downscaled the model with the inverse distance-weighted method. Databases of herbaria specimens, genetic algorithms (GARP), and digital covers of biophysical variables that affect oaks and pines were used to project geographic distributions of the species under a severe and conservative scenario of climate change for the year 2050. Starting with the current average temperature of 20.2 °C and average precipitation of 793 mm, under the severe warming scenario mean temperature and precipitation changed to 22.7 °C and 660 mm, respectively, in 2050. For the conservative warming scenario, these variables shifted to 21.8 °C and 721 mm. Responses to the different scenarios of climate change were predicted to be species-specific and related to each species climate affinity. The current geographic distribution of oaks and pines decreased 7-48% and 0.2-64%, respectively. The more vulnerable pines were Pinus rudis, P. chihuahuana, P. oocarpa, and P. culminicola, and the most vulnerable oaks were Quercus crispipilis, Q. peduncularis, Q. acutifolia, and Q. sideroxyla. In addition to habitat conservation, we think sensitive pine and oak species should be looked at more closely to define ex situ strategies (i.e., seed preservation in germplasm banks) for their long-term conservation. Modeling climatic-change scenarios is important to the development of conservation strategies.

Estimating potential changes in future flood patterns based on anticipated changes in hydrological characteristics within the basin is crucial for mitigating flood damage and managing flood risk. In this study, nonparametric probability models are used to estimate future rainfall patterns in Seoul under the GCM‐based climate change scenarios (CCS), and the estimated future daily rainfall data was temporally downscaled to hourly units using the KNNR‐GA technique. Changes in flood hazard and runoff characteristics of the target area based on the estimated future rainfall data are quantitatively assessed. The results highlight that under CCS, flood runoff may increase further into the future, resulting in more significant changes in flood patterns and accelerating the increase in flood hazard. The delta change factor of flood risk indicators increased relatively significantly in more severe CCS. This study also proposed a process to estimate future flood runoff and mitigation effects according to CCS by reflecting various flood mitigation measures in the urban drainage system model. These findings can offer valuable insights for setting the direction of current and future mitigation measures.

The distribution shift of forest species due to the fact of climate change may negatively affect ecosystem services including the production of medicinal resources. Climate change impact assessments of habitat range changes are essential to sustainably manage forest resources. A change in the habitat suitability due to the fact of climate change was predicted for Angelica gigas, which has high economic value among forest medicinal resources in South Korea. The habitat suitability was predicted by an ensemble species distribution model that combined the results of nine single algorithm models using the committee averaging method. A total 168 occurrence data and 10 environmental variables were used for the single algorithm models. The area under the receiver operation characteristic curve (AUC) and true skill statistic (TSS) were applied to evaluate the models’ performance, and the contribution of the environmental variables was calculated as an important value for each single algorithm model. Climate change scenarios were projected to predict future habitat suitability. The future suitable habitat for A. gigas was gradually reduced to the high mountain regions of the eastern part of South Korea regardless of the climate change scenarios. The main environmental variable was the annual mean temperature, and the rise in temperature due to the fact of climate change was found to have a negative effect on the habitat suitability for A. gigas. The decline in the habitat suitability for A. gigas, a major forest medicinal resource, is expected to result in the reduction in its production. Therefore, it is required to establish adaptation measures to mitigate the negative impact of this decrease, such as protecting the natural habitats of A. gigas.

The increasing resilience to climate change in the agricultural sector report presents local-level priorities, informed by stakeholder input, to build agricultural resilience in both countries. The objectives of this study were threefold: (1) to improve the understanding of climate change projections and impacts on rural communities and livelihoods in selected regions of Jordan and Lebanon, specifically the Jordan River Valley and Lebanon's Bekaa Valley; (2) to engage local communities, farmers, local experts, and local and national government representatives in a participatory fashion in helping craft agricultural adaptation options to climate change; and (3) to develop local and regional climate change action plans that formulate recommendations for investment strategies and strategic interventions in local agricultural systems. The climate challenges confronting development in the Middle East are particularly stark. This region, and in particular its rural people, face what might be called a \"triple threat\" from climate change. First, the Middle East is already one of the driest and most water-scarce regions of the world (World Bank 2011a) and faces severe challenges posed by high temperatures and limited water supplies. This report to assist Jordan and Lebanon in understanding the specific challenges and opportunities posed by climate change in the agricultural sector.

Because of multifunctional weirs installed as part of large river regulation works in Korea, water quality problems have arisen from environmental changes in tandem with decreased flow rates. However, there has been limited research into the green algae removal effect, water quality improvement in congested waters, dam and weir operations, and consequential riverbed changes. Studies regarding outflow in a basin, the application and development of sediment load output analysis methods, feasibility of related dam operations, and riverbed patterns have been separately performed. However, basins and rivers should be analyzed by an integrated method instead of an individual one. Therefore, in the present study, the effect of congestion on a river connected to a dam/weir and estuary bank was analyzed based on climate change scenarios HadGEM3-RA RCP 4.5 and 8.5, with the aim of integrating individual studies using watershed and river models. Flow was controlled by dam- and weir-related discharge simulations. Variations in the riverbed caused by the transfer of suspended load in the downstream region were analyzed for both long and short durations. The results of this analysis suggest that given future climate change scenarios, the width of the river and riverbed variations in the riverbed are expected to rise.

The study aimed to find out possible changes in climatic data (temperature and rainfall) from the regional climate model viz. PRECIS(Providing Regional Climates for Impact Studies)under different SRES scenarios (A1B, A2 and B2 scenario) by the mid (2021-2050) and end (2071-2100) century at six locations of Punjab representing different agroclimatic zones and to study their impact on maize yield using the crop growth simulation model.The results revealed that the different zones of the state are expected to bewarmer during the mid century and this trend has been projected to continue by the end of century because of increase in maximum and minimum temperature at all the locations.The CERES-Maize simulated significant decrease in duration and grain yield of maize crop under projected climate scenarios. The reduction in the crop duration and grain yield was found to be more under the A1B and A2 scenario (high emission scenario) followed by B2 scenario (low emission scenario)due to adverse effects on crop physiology.