The influence of global climate and local hydrological features over streamflow extremes.  Case of study in a tropical Andean basin

2021 ◽  
Author(s):  
Alex Avilés ◽  
Juan Contreras ◽  
Daniel Mendoza ◽  
Jheimy Pacheco
Keyword(s):  
Global Climate ◽  
Standardized Precipitation Index ◽  
Additive Models ◽  
Mitigation Strategies ◽  
Climate Indices ◽  
Local Climate ◽  
Climate Conditions ◽  
Lulc Changes ◽  
Daily Streamflow ◽  
Floods And Droughts

<p>Hydrological extremes such as floods and droughts are the most common and threatening natural disasters worldwide. Particularly, tropical Andean headwaters systems are prone to hazards due to their complex climate conditions. However, little is known about the underlying mechanisms triggering such extremes events. In this study, the Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used for investigating the relations between the Annual- Peak-Flows (APF) and Annual-Low-Flows (ALF), respecting to climate and land use/land cover (LULC) changes. Thirty years of daily streamflow data-sets taken from two Andean catchments of southern Ecuador are used for the experimental research. Global climate indices (CI), describing the large-scale climate variability were used as hypothetical drivers explaining the extreme’s variations on streamflow measures. Additionally, the Antecedent-Cumulative-Precipitation (AP) and the Standardized-Precipitation-Index (SPI), and LULC percentages were also included as possible direct drivers – synthetizing local climate conditions and localized hydrological changes. The results indicate that AP and SPI clearly explain the extreme streamflow variability. Nonetheless, global variables play a significant role underneath the local climate. For instance, ENSO and CAR exert influence over the APF, while ENSO, TSA, PDO and AMO control ALF. Furthermore, it was found that LULC changes strongly influence both extremes; although this is particularly important for relative more disturbed catchments. These results provide valuable insights for future forecasting of floods and droughts based on precipitation and climate indices, and for the development of mitigation strategies for mountain catchments.</p>

scholarly journals The influence of global climate and local hydrological variations over streamflow extremes: The tropical-mountain case

2019 ◽  
Author(s):  
Juan Contreras ◽  
Daniel Mendoza ◽  
Jheimy Pacheco ◽  
Alex Avilés
Keyword(s):  
Global Climate ◽  
Standardized Precipitation Index ◽  
Additive Models ◽  
Mitigation Strategies ◽  
Climate Indices ◽  
Local Climate ◽  
Climate Conditions ◽  
Lulc Changes ◽  
Daily Streamflow ◽  
Floods And Droughts

Abstract. Hydrological extremes such as floods and droughts are the most common and threatening natural disasters worldwide. Particularly, tropical Andean headwaters systems are prone to hazards due to their complex climate conditions. However, little is known about the underlying mechanisms triggering such extremes events. In this study, the Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used for investigating the relations between the Annual-Peak-Flows (APF) and Annual-Low-Flows (ALF), respecting to climate and land use/land cover (LULC) changes. Thirty years of daily streamflow data-sets taken from two Andean catchments of southern Ecuador are used for the experimental research. Global climate indices (CI), describing the large-scale climate variability were used as hypothetical drivers explaining the extreme's variations on streamflow measures. Additionally, the Antecedent-Cumulative-Precipitation (AP) and the Standardized-Precipitation-Index (SPI), and LULC percentages were also included as possible direct drivers – synthetizing local climate conditions and localized hydrological changes. The results indicate that AP and SPI clearly explain the extreme streamflow variability. Nonetheless, global variables play a significant role underneath the local climate. For instance, ENSO and CAR exert influence over the APF, while ENSO, TSA, PDO and AMO control ALF. Furthermore, it was found that LULC changes strongly influence both extremes; although this is particularly important for relative more disturbed catchments. These results provide valuable insights for future forecasting of floods and droughts based on precipitation and climate indices, and for the development of mitigation strategies for mountain catchments.

scholarly journals Synergistic impacts of global warming and thermohaline circulation collapse on amphibians

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Julián A. Velasco ◽  
Francisco Estrada ◽  
Oscar Calderón-Bustamante ◽  
Didier Swingedouw ◽  
Carolina Ureta ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Thermohaline Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Extinction Risk ◽  
Meridional Overturning Circulation ◽  
Mitigation Strategies ◽  
Amphibian Species ◽  
Climate Conditions

AbstractImpacts on ecosystems and biodiversity are a prominent area of research in climate change. However, little is known about the effects of abrupt climate change and climate catastrophes on them. The probability of occurrence of such events is largely unknown but the associated risks could be large enough to influence global climate policy. Amphibians are indicators of ecosystems’ health and particularly sensitive to novel climate conditions. Using state-of-the-art climate model simulations, we present a global assessment of the effects of unabated global warming and a collapse of the Atlantic meridional overturning circulation (AMOC) on the distribution of 2509 amphibian species across six biogeographical realms and extinction risk categories. Global warming impacts are severe and strongly enhanced by additional and substantial AMOC weakening, showing tipping point behavior for many amphibian species. Further declines in climatically suitable areas are projected across multiple clades, and biogeographical regions. Species loss in regional assemblages is extensive across regions, with Neotropical, Nearctic and Palearctic regions being most affected. Results underline the need to expand existing knowledge about the consequences of climate catastrophes on human and natural systems to properly assess the risks of unabated warming and the benefits of active mitigation strategies.

scholarly journals Evaluating the Tourist Climate Comfortable Period of China in a Changing Climate

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dan-Dan Yu ◽  
Shan Li ◽  
Zhong-Yang Guo
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Scientific Evidence ◽  
Climatic Conditions ◽  
Climate Index ◽  
Climate Indices ◽  
Climate Data ◽  
Climate Conditions ◽  
Positive Effects ◽  
Changing Climate

The evaluation of climate comfort for tourism can provide information for tourists selecting destinations and tourism operators. Understanding how climate conditions for tourism evolve is increasingly important for strategic tourism planning, particularly in rapidly developing tourism markets like China in a changing climate. Multidimensional climate indices are needed to evaluate climate for tourism, and previous studies in China have used the much criticized “climate index” with low resolution climate data. This study uses the Holiday Climate Index (HCI) and daily data from 775 weather stations to examine interregional differences in the tourist climate comfortable period (TCCP) across China and summarizes the spatiotemporal evolution of TCCP from 1981 to 2010 in a changing climate. Overall, most areas in China have an “excellent” climate for tourism, such that tourists may visit anytime with many choices available. The TCCP in most regions shows an increasing trend, and China benefits more from positive effects of climate change in climatic conditions for tourism, especially in spring and autumn. These results can provide some scientific evidence for understanding human settlement environmental constructions and further contribute in improving local or regional resilience responding to global climate change.

scholarly journals SI: Survivability under Overheating: The Impact of Regional and Global Climate Change on the Vulnerable and Low-Income Population

Climate ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 122
Author(s):  
Afroditi Synnefa ◽  
Shamila Haddad ◽  
Priyadarsini Rajagopalan ◽  
Mattheos Santamouris
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Low Income ◽  
Underserved Populations ◽  
Global Climate ◽  
Mitigation Strategies ◽  
Local Climate ◽  
Low Income Population ◽  
Local Climate Change ◽  
The Impact

The present special issue discusses three significant challenges of the built environment, namely regional and global climate change, vulnerability, and survivability under the changing climate. Synergies between local climate change, energy consumption of buildings and energy poverty, and health risks highlight the necessity to develop mitigation strategies to counterbalance overheating impacts. The studies presented here assess the underlying issues related to urban overheating. Further, the impacts of temperature extremes on the low-income population and increased morbidity and mortality have been discussed. The increasing intensity, duration, and frequency of heatwaves due to human-caused climate change is shown to affect underserved populations. Thus, housing policies on resident exposure to intra-urban heat have been assessed. Finally, opportunities to mitigate urban overheating have been proposed and discussed.

scholarly journals MODEL DEBIT DAERAH ALIRAN SUNGAI JANGKOK BERDASARKAN HASIL PREDIKSI MODEL STATISTICAL DOWNSCALING NONPARAMETRIK KERNEL CURAH HUJAN DAN TEMPERATUR

2019 ◽  
Vol 12 (2) ◽  
pp. 236
Author(s):  
Mustika Hadijati ◽  
Irwansyah Irwansyah
Keyword(s):  
River Water ◽  
Statistical Downscaling ◽  
Global Climate ◽  
Water Discharge ◽  
Develop Model ◽  
Statistical Downscaling Model ◽  
Local Climate ◽  
Climate Conditions ◽  
Cart Algorithm ◽  
Local Rainfall

River water discharge is important information for water resources management planning, so it is necessary to develop river water discharge model as basis of its predictions. In order to get the result of predictions of river water discharge with high accuracy, it is developed a model of river water discharge based on the predictions of local climate (local rainfall and temperature) that are influenced by global climate conditions. Prediction of local climate is based on the Kernel nonparametric statistical downscaling model by utilizing GCM data. GCM data is a high dimensional global data, so data pre-processing is needed to reduce data dimension. It is done by CART algorithm. Statistical downscaling model is used to predict local rainfall and temperature. The prediction results are quite good with relatively small RMSE value. They are used to develop model of river water discharge. Modeling river water discharge is carried out using the Kernel nonparametric approach. The model of river water discharge produced is quite good because it can be used to predict river water discharge with relatively small RMSE.

scholarly journals REVIEW : PENGARUH PEMANASAN GLOBAL TERHADAP INTENSITAS SERANGAN KUTU KEBUL (Bemisia tabbaci Genn ) DAN CARA PENGENDALIANNYA PADA TANAMAN KEDELAI

BUANA SAINS ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 99-110
Author(s):  
I Made Indra Agastya ◽  
Reza Prakoso Dwi Julianto ◽  
Marwoto Marwoto
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Global Climate Change ◽  
Agricultural Development ◽  
Global Climate ◽  
Metabolic System ◽  
Local Climate ◽  
Climate Conditions ◽  
Soybean Pest ◽  
The Impact

Global warming has changed global, regional and local climate conditions. Global climate change is caused, among others, by the increase in greenhouse gas emissions (GHG) due to various activities that drive the increase in the earth's temperature. Given that climate is a key element in the metabolic system, plant physiology and crop ecosystems, global climate change will adversely affect the sustainability of agricultural development. The impact of global climate change is the increasing population of pests on agricultural crops. One of the soybean pests whose population is increasing due to the increase in air temperature is the Bemisia tabbaci infestation. Increased pest populations of Bemesia tabbaci infestation in soybean crops cause dwarf leaves of dwarf plants and threatens to increase soybean production. Efforts to overcome the impact of global warming is mainly due to increased pest populations, it is necessary to think and seek breakthroughs to anticipate the explosion of pest populations in soybean crops, among others by: the optimization of natural control, physical and mechanical control and cultivation techniques. The combination of techniques or tactics of the optimal component of soybean pest control technology is established on the basis of appropriate information knowledge about soybean pest, ecosystem and socio-economic based on IPM approach.

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 207
Author(s):  
Javier Gómez-Gómez ◽  
Rafael Carmona-Cabezas ◽  
Elena Sánchez-López ◽  
Eduardo Gutiérrez de Ravé ◽  
Francisco José Jiménez-Hornero
Keyword(s):  
Complex Networks ◽  
Global Climate ◽  
Spatial Relation ◽  
Clustering Coefficient ◽  
Horizontal Visibility ◽  
Climate Conditions ◽  
Mean Values ◽  
Intrinsic Nature ◽  
Temperature Anomalies ◽  
Mean Temperature

The last decades have been successively warmer at the Earth’s surface. An increasing interest in climate variability is appearing, and many research works have investigated the main effects on different climate variables. Some of them apply complex networks approaches to explore the spatial relation between distinct grid points or stations. In this work, the authors investigate whether topological properties change over several years. To this aim, we explore the application of the horizontal visibility graph (HVG) approach which maps a time series into a complex network. Data used in this study include a 60-year period of daily mean temperature anomalies in several stations over the Iberian Peninsula (Spain). Average degree, degree distribution exponent, and global clustering coefficient were analyzed. Interestingly, results show that they agree on a lack of significant trends, unlike annual mean values of anomalies, which present a characteristic upward trend. The main conclusions obtained are that complex networks structures and nonlinear features, such as weak correlations, appear not to be affected by rising temperatures derived from global climate conditions. Furthermore, different locations present a similar behavior and the intrinsic nature of these signals seems to be well described by network parameters.

Diatoms in Saline Lakes Paleoclimate and Paleoecology Interpretations

2007 ◽  
Vol 13 ◽  
pp. 149-168 ◽  
Author(s):  
Erik J. Ekdahl
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Global Climate Change ◽  
Water Conservation ◽  
Environmental Changes ◽  
Global Climate ◽  
Light Availability ◽  
Ionic Concentration ◽  
Mitigation Strategies ◽  
Environmental Response

Average global temperatures are predicted to rise over the next century and changes in precipitation, humidity, and drought frequency will likely accompany this global warming. Understanding associated changes in continental precipitation and temperature patterns in response to global change is an important component of long-range environmental planning. For example, agricultural management plans that account for decreased precipitation over time will be less susceptible to the effects of drought through implementation of water conservation techniques.A detailed understanding of environmental response to past climate change is key to understanding environmental changes associated with global climate change. To this end, diatoms are sensitive to a variety of limnologic parameters, including nutrient concentration, light availability, and the ionic concentration and composition of the waters that they live in (e.g. salinity). Diatoms from numerous environments have been used to reconstruct paleosalinity levels, which in turn have been used as a proxy records for regional and local paleoprecipitation. Long-term records of salinity or paleoprecipitation are valuable in reconstructing Quaternary paleoclimate, and are important in terms of developing mitigation strategies for future global climate change. High-resolution paleoclimate records are also important in groundtruthing global climate simulations, especially in regions where the consequences of global warming may be severe.

scholarly journals Experimental comparison of two methods to study barley responses to partial submergence

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Alexandra Miricescu ◽  
Tomás Byrne ◽  
Catherine M. Doorly ◽  
Carl K. Y. Ng ◽  
Susanne Barth ◽  
...  
Keyword(s):  
Global Climate ◽  
Experimental Comparison ◽  
Soil Conditions ◽  
Early Developmental Stage ◽  
Starch Solution ◽  
Waterlogging Tolerance ◽  
Climate Conditions ◽  
Flooding Events ◽  
Staple Crop ◽  
Early Developmental

Abstract Background Crop yield is dependent on climate conditions, which are becoming both more variable and extreme in some areas of the world as a consequence of global climate change. Increased precipitation and flooding events are the cause of important yield losses due to waterlogging or (partial) submergence of crops in the field. Our ability to screen efficiently and quickly for varieties that have increased tolerance to waterlogging or (partial) submergence is important. Barley, a staple crop worldwide, is particularly sensitive to waterlogging. Screening for waterlogging tolerant barley varieties has been ongoing for many years, but methods used to screen vary greatly, from the type of soil used to the time at which the treatment is applied. This variation makes it difficult to cross-compare results. Results Here, we have devised a scoring system to assess barley tolerance to waterlogging and compare two different methods when partial submergence is applied with either water or a starch solution at an early developmental stage, which is particularly sensitive to waterlogging or partial submergence. The use of a starch solution has been previously shown to result in more reducing soil conditions and has been used to screen for waterlogging tolerance. Conclusions Our results show that the two methods provide similar results to qualitatively rank varieties as tolerant or sensitive, while also affecting plants differently, in that application of a starch solution results in stronger and earlier symptoms than applying partial submergence with water.

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