A new spatiotemporal two-stage standardized weighted procedure for regional drought analysis.

Drought is a complex phenomenon that occurs due to insufficient precipitation. It does not have immediate effects, but sustained drought can affect the hydrological, agriculture, economic sectors of the country. Therefore, there is a need for efficient methods and techniques that properly determine drought and its effects. Considering the significance and importance of drought monitoring methodologies, a new drought assessment procedure is proposed in the current study, known as the Maximum Spatio-Temporal Two-Stage Standardized Weighted Index (MSTTSSWI). The proposed MSTTSSWI is based on the weighting scheme, known as the Spatio-Temporal Two-Stage Standardized Weighting Scheme (STTSSWS). The potential of the weighting scheme is based on the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and the steady-state probabilities. Further, the STTSSWS computes spatiotemporal weights in two stages for various drought categories and stations. In the first stage of the STTSSWS, the SPI, SPEI, and the steady-state probabilities are calculated for each station at a 1-month time scale to assign weights for varying drought categories. However, in the second stage, these weights are further propagated based on spatiotemporal characteristics to obtain new weights for the various drought categories in the selected region. The STTSSWS is applied to the six meteorological stations of the Northern area, Pakistan. Moreover, the spatiotemporal weights obtained from STTSSWS are used to calculate MSTTSSWI for regional drought characterization. The MSTTSSWI may accurately provide regional spatiotemporal characteristics for the drought in the selected region and motivates researchers and policymakers to use the more comprehensive and accurate spatiotemporal characterization of drought in the selected region.

Monthly drought prediction based on ensemble models.

Drought is a natural hazard, which is a result of a prolonged shortage of precipitation, high temperature and change in the weather pattern. Drought harms society, the economy and the natural environment, but it is difficult to identify and characterize. Many areas of Pakistan have suffered severe droughts during the last three decades due to changes in the weather pattern. A drought analysis with the incorporation of climate information has not yet been undertaken in this study region. Here, we propose an ensemble approach for monthly drought prediction and to define and examine wet/dry events. Initially, the drought events were identified by the short term Standardized Precipitation Index (SPI-3). Drought is predicted based on three ensemble models i.e., Equal Ensemble Drought Prediction (EEDP), Weighted Ensemble Drought Prediction (WEDP) and the Conditional Ensemble Drought Prediction (CEDP) model. Besides, two weighting procedures are used for distributing weights in the WEDP model, such as Traditional Weighting (TW) and the Weighted Bootstrap Resampling (WBR) procedure. Four copula families (i.e., Frank, Clayton, Gumbel and Joe) are used to explain the dependency relation between climate indices and precipitation in the CEDP model. Among all four copula families, the Joe copula has been found suitable for most of the times. The CEDP model provides better results in terms of accuracy and uncertainty as compared to other ensemble models for all meteorological stations. The performance of the CEDP model indicates that the climate indices are correlated with a weather pattern of four meteorological stations. Moreover, the percentage occurrence of extreme drought events that have appeared in the Multan, Bahawalpur, Barkhan and Khanpur are 1.44%, 0.57%, 2.59% and 1.71%, respectively, whereas the percentage occurrence of extremely wet events are 2.3%, 1.72%, 0.86% and 2.86%, respectively. The understanding of drought pattern by including climate information can contribute to the knowledge of future agriculture and water resource management.

Evaluation of wet and dry event's trend and instability based on the meteorological drought index.

A temporal imbalance in the water availability, which is consistently below average or more than average rainfall, can lead to extremely dry or wet conditions. This impacts on agricultural yields, water resources and human activities. Weather instabilities and trends of wet/dry events have not yet been explored in Pakistan. In this study, we have two-fold objectives: (1) evaluate the weather instabilities, and (2) the trend of dry/wet events of selected stations of Pakistan. To observe weather instabilities, we used Mean Marginal Hilbert Spectrum (MMHS) and Continuous Wavelet Power Spectrum (CWPS) as meteorological series are mostly non-linear and non-stationary. We used Ensemble Empirical Mode Decomposition (EEMD) for the analysis of temporal characteristics of dry/wet events. We found that all stations are facing severe weather instabilities during the short period of 5 and 10 months using MMHS method and CWPS has shown the weather instabilities during 4 to 32 months of periodicity for all stations. Ultimately, the achieved short-term weather instabilities indicated by MMHS is consistent with CWPS. In summary, these findings might be useful for water resource management and policymakers.

Bayesian network based procedure for regional drought monitoring: The Seasonally Combinative Regional Drought Indicator.

Drought is a complex natural hazard. It occurs due to a prolonged period of deficient in rainfall amount in a certain region. Unlike other natural hazards, drought hazard has a recurrent occurrence. Therefore, comprehensive drought monitoring is essential for regional climate control and water management authorities. In this paper, we have proposed a new drought indicator: the Seasonally Combinative Regional Drought Indicator (SCRDI). The SCRDI integrates Bayesian networking theory with Standardized Precipitation Temperature Index (SPTI) at varying gauge stations in various month/seasons. Application of SCRDI is based on five gauging stations of Northern Area of Pakistan. We have found that the proposed indicator accounts the effect of climate variation within a specified territory, accurately characterizes drought by capturing seasonal dependencies in geospatial variation scenario, and reduces the large/complex data for future drought monitoring. In summary, the proposed indicator can be used for comprehensive characterization and assessment of drought at a certain region.

Achieving environmental sustainability through information technology: "Digital Pakistan" initiative for green development.

The importance of information and communication technologies (ICTs) in environmental resource management opens a new debate for the policy makers in order to promote green technologies to mitigate high mass carbon emissions across the globe. "Digital Pakistan" initiative is taken by the government that aimed to use technology for country's social welfare, which further be enhance for achieving environmental sustainability over a time horizon. This study examined the long-run relationship between ICTs, energy demand, and carbon emissions in a context of Pakistan by using a time series data from 1975 to 2017. The results show that energy demand increases economic growth in the short-run while it decreases economic growth in the long-run. The country's economic growth substantially increases along with an increase in trade openness and mobile-telephone subscription (ICTs) in the short-run; however, the result is changed in the long-run due to increase in carbon emissions in a given time period. The results provoke that continued economic growth and ICT penetration substantially decreases energy demand, whereas urbanization increases energy demand in a country. The results show that variations in emissions associated with proportionate changes in ICTs penetration, economic growth, energy demand, and population growth. Human capital, trade openness, and energy demand are the significant drivers of ICT penetration in a country. The study concludes that the use of green technology is imperative for achieving long-term sustainable growth in a country.

Dynamic linkages between tourism, energy, environment, and economic growth: evidence from top 10 tourism-induced countries.

The importance of sustainable tourism in environmental literature is well documented, while there is a need to explore its different socio-economic and environmental factors that are helpful to promote sustainable development across countries. The objective of the study is to investigate the relationship between international tourism (ITOUR), energy demand (ED), carbon dioxide emissions (CO2), and economic growth (EG) by using a panel data of top 10 tourism-induced countries for the period of 1995-2016. The findings confirmed the Environmental Kuznets Curve (EKC) hypothesis in the panel of top 10 countries. Moreover, the results show that FDI inflows negatively influenced natural environment in the form of high mass carbon emissions, which supported "pollution haven hypothesis (PHH)." The energy demand escalates carbon emissions across countries. The study confirmed the feedback relationship between (i) tourism income (TI) and ED, and (ii) CO2 emissions and international tourism departures (ITD), while study supported the growth-led tourism income across countries. The study concludes that government(s) should have to focus on ecotourism policies and energy resources in a way to mitigate carbon emissions that is imperative for sustainable development across countries.

Socio-economic and environmental factors influenced pro-poor growth process: new development triangle.

The developmental triangle earlier comprises economic growth, income inequality, and poverty, while in this study, we extended it by incorporating environmental and resource factors, health and education factors, sectoral value added, and some other growth-specific factors for assessing pro-poor growth, by considering Bolivian economy as a case study. The elasticity estimates show that agriculture and industrial sector growth is not pro-poor due to account of high income inequality, while services sector played a vital role in country's economic development and supports poor livelihood in a country. Energy and environmental resources negatively impact on quality of life of the poor relative to non-poor, which create income differences among them. Health and education expenditures give favors to the poor and supported the notion of pro-poor growth, while country's per capita income and foreign direct investment inflows increase income inequality that lead towards pro-rich growth. The results conclude that, in general, Bolivian economy growth is fairly unstable, polluted, and unhealthy that biased to the poor relative to non-poor.

Economics of death and dying: a critical evaluation of environmental damages and healthcare reforms across the globe.

The economics of death and dying highlighted that environmental factors negatively influence healthcare sustainability. Therefore, this study conducted a system-based literature review to identify the negative externality of environmental damages on global healthcare reforms. Based on 42 peer-reviewed papers in the field of healthcare reforms and 12 papers in the field of environmental hazards, we identified 25 factors associated with death and dying and 15 factors associated with health-related damages across the world respectively. We noted that environmental factors are largely responsible to affect healthcare sustainability reforms by associating with the number of healthcare diseases pertaining to air pollutants. The study suggests healthcare practitioners and environmentalists to devise long-term sustainable healthcare policies by limiting highly toxic air pollutants through technology-embodied green healthcare infrastructure to attained efficient global healthcare recovery.

Green is clean: the role of ICT in resource management.

It is well documented that carbon emissions can be reduced by replacing conventional energy resources with renewable energy resources; thereby, the role of green technology is essential as it protect natural environment. Given that, the United Nations' agenda of "green is clean" may be achievable by adoption of green technologies. The objective of the study is to examine the link between information and communication technology (ICT), economic growth, energy consumption, and carbon dioxide (CO2) emissions in the context of South Korean economy, by using a novel Morlet wavelet approach. The study applies continuous wavelet power spectrum, the wavelet coherency, and the partial and the multiple wavelet coherency to the year during 1973-2016. The outcomes reveal that the connections among the stated variables progress over frequency and time domain. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages. From the time-domain sight, the results display robust but not consistent associations among the considered variables. From an economic point sight, the wavelet method displays that ICT helps to reduce environmental degradation in a medium and long run in the South Korean economy. This emphasizes the significance of having organized strategies by the policymakers to cope up with 2 to 3 years of the occurrence of the huge environmental degradation in South Korea.

Natural disasters and economic losses: controlling external migration, energy and environmental resources, water demand, and financial development for global prosperity.

The objective of the study is to examine the impact of natural disasters on external migration, price level, poverty incidence, health expenditures, energy and environmental resources, water demand, financial development, and economic growth in a panel of selected Asian countries for a period of 2005-2017. The results confirm that natural disasters in the form of storm and flood largely increase migration, price level, and poverty incidence, which negatively influenced country's economic resources, including enlarge healthcare expenditures, high energy demand, and low economic growth. The study further presented the following results: i) natural resource depletion increases external migration, ii) FDI inflows increase price level, iii) increase healthcare spending and energy demand decreases poverty headcount, iv) poverty incidence and mortality rate negatively influenced healthcare expenditures, v) industrialization increases energy demand, and vi) agriculture value added, fertilizer, and cereal yields required more water supply to produce greater yield. The study emphasized the need to magnify the intensity of natural disasters and create natural disaster mitigation unit to access the human and infrastructure cost and attempt quick recovery for global prosperity.

Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator.

Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions; however, they give good approximation usually in time. The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. The genetic algorithm depends on selection criteria, crossover, and mutation operators. To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations. In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance. This approach has been linked with path representation, which is the most natural way to represent a legal tour. Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements.