Vulnerability and impact assessment of extreme climatic event: A case study of southern Punjab, Pakistan

Assessing spatiotemporal trends of total and extreme precipitation in a subtropical highland region: A climate perspective

This study used a dataset of 30 years (1990-2020) of daily observations from 24 meteorological stations in the northern highlands of Pakistan to assess trends in extreme precipitation indices. The RClimDex model was used to analyze the indices, and the Modified Mann-Kendal test and the Theil-Sen slope estimator were applied to determine trends and slopes, respectively. The results showed a significant decrease in total annual precipitation amount (PRCPTOT) with varying rates of negative trend from -4.44 mm/year to -19.63 mm/year. The total winter and monsoon precipitation amounts were also decreased during the past three decades. The intensity-based precipitation indices (RX1Day, RX5Day, R95p, R99p, and SDII) showed a significant decrease in extreme intensity events over time, while the count of consecutive dry days (CDD) and consecutive wet days (CWD) indicated a significant decrease in duration at multiple stations. The annual counts of days with precipitation more than or equal to 10 mm (R10), 20 mm (R20), and 25 mm (R25) exhibited a significant decrease in frequency of extreme precipitation events, with the decrease more pronounced in the northern parts of the study domain. The findings of this study indicate a significant decline in the intensity, frequency, and extent of precipitation extremes across the northern highlands of Pakistan over the past 30 years.

Do farmers' risk perception, adaptation strategies, and their determinants benefit towards climate change? Implications for agriculture sector of Punjab, Pakistan

Due to global and regional climatic dynamics for a couple of decades, agricultural productivity, rural livelihood, and food security have been badly affected in Pakistan. This study was conducted in Punjab, Pakistan, to explore the farmers' understanding of the impacts of climate change, adaptation strategies, determinants, and benefits on agriculture using data from 1080 respondents. Perceived risks by the farmers in the rice-wheat cropping system and the cotton-wheat cropping system were weed infestation, seed rate augmented, low-quality seeds, infestation of crop diseases and pests, change of cropping pattern, increase of input use, decrease of cropping intensity and productivity, decreasing soil fertility, increasing irrigation frequency, and increase of harvesting time. To alleviate the adverse influences of climate change, the adaptation strategies used by farmers were management of crop and variety, soil and irrigation water, diversification of agriculture production systems and livelihood sources, management of fertilizer and farm operations time, spatial adaptation, access to risk reduction measures and financial assets, adoption of new technologies, institutional support, and indigenous knowledge. Moreover, the results of Binary Logistic Regression indicate that adaptation strategies are affected by different factors like age, education, household family size, off-farm income, remittances, credit access, information on climatic and natural hazards, information on weather forecasting, land acreage, the experience of growing crops and rearing of livestock, tenancy status, tube well ownership, livestock inventory, access to market information, agricultural extension services, and distance from agricultural input/output market. There is a significant difference between adapters and nonadapters. The risk management system may be created to protect crops against failures caused by extreme weather events. There is a need to develop crop varieties that are both high yielding and resistant to climate change. Moreover, cropping patterns should be revised to combat the effects of climate change. To enhance farmers' standard of living, it is necessary to provide adequate extension services and a more significant number of investment facilities. These measures will assist farmers in maintaining their standard of living and food security over the long term to adapt to the effects of climate change based on various cropping zones.

Rural Household Differentiation and Poverty Vulnerability: An Empirical Analysis Based on the Field Survey in Hubei, China

Rural family differentiation is an important perspective to analyze farmers’ behavior and poverty. Based on the data of 1673 farm households from rural field survey in 2019 in Hubei Province of China, this paper examines the main influencing factors of farm household differentiation on farm household poverty vulnerability from the perspective of the sustainable livelihoods of farm households. On this basis, the contribution of each influencing factor to farm household poverty vulnerability is analysed using the regression decomposition method. The results of the study show that the variables of farm household differentiation have a significant impact on poverty vulnerability, and the net household income per capita, which reflect the vertical differentiation of farm households, and the proportion of non-farm labor, which reflects the horizontal differentiation of farm households. Both have a significant negative impact on the poverty vulnerability of farm households. The regression decomposition method shows that the proportion of non-farm labor force, which reflects the horizontal differentiation of farm households, has the highest contribution to the poverty vulnerability of farm households. Human capital, natural capital, social capital, and physical capital also influence the poverty vulnerability of farm households to a certain extent.

How do climatic change, cereal crops and livestock production interact with carbon emissions? Updated evidence from China

Carbon dioxide emission and climatic variation have a detrimental influence on the atmosphere as well as on agriculture production. The key aim of the present study was to investigate the influence of carbon dioxide emission on livestock, cereal crops production, rainfall and temperature in China by utilizing the vector autoregressive model and Granger causality test for the period 1988-2017. Variables stationarity was verified by using ADF, P-P and KPSS unit root tests. The outcomes through long-run dynamics exposed that agriculture value added and rainfall have a positive influence on carbon dioxide emission, while cereal crops production, livestock production and temperature have an adverse interaction with carbon dioxide emission. Similarly, the results of the short-run analysis also demonstrate that agriculture value added, cereal crops production, livestock production, rainfall and temperature have a significant influence on carbon dioxide emission with their p-values (0.0488), (0.0885), (0.0263), (0.0096) and (0.5141) respectively. Furthermore, the Granger causality test outcomes also exposed a unidirectional linkage amid the variables. In order to improve agricultural productivity, the Chinese government should take potential steps to minimize the carbon dioxide emission from various industries that trigger climate change.

Urban Resilience of Shenzhen City under Climate Change

The Chinese government attaches great importance to climate change adaptation and has issued relevant strategies and policies. Overall, China’s action to adapt to climate change remains in its infancy, and relevant research needs to be further deepened. In this paper, we study the future adaptive countermeasures of Shenzhen city in the Pearl River Delta in terms of climate change, especially urban flood risk resilience. Based on the background investigation of urban flood risk in Shenzhen, this paper calculates the annual precipitation frequency of Shenzhen from 1953 to 2020, and uses the extreme precipitation index as a quantitative indicator to analyze the changes in historical precipitation and the impact of major flood disasters in Shenzhen city in previous decades. Based on the six kinds of model data of the scenario Model Inter-comparison Project (MIP) in the sixth phase of the Coupled Model Inter-comparison Project (CMIP6), uses the Taylor diagram and MR comprehensive evaluation method to evaluate the ability of different climate models to simulate extreme precipitation in Shenzhen, and the selected models are aggregated and averaged to predict the climate change trend of Shenzhen from 2020 to 2100. The prediction results show that Shenzhen will face more severe threats from rainstorms and floods in the future. Therefore, this paper proposes a resilience strategy for the city to cope with the threat of flood in the future, including constructing a smart water management system and promoting the development of a sponge city. Moreover, to a certain extent, it is necessary to realize risk transfer by promoting a flood insurance system.

Spatiotemporal variations and driving factors of dust storm events in northern China based on high-temporal-resolution analysis of meteorological data (1960-2007)

Northern China is a significant source of dust source in Central Asia. Thus, high-resolution analysis of dust storms and comparison of dust sources in different regions of northern China are important to clarify the formation mechanism of East Asian dust storms and predict or even prevent such storms. Here, we analyzed spatiotemporal trends in dust storms that occurred in three main dust source regions during 1960-2007: Taklimakan Desert (western region [WR]), Badain Jaran and Tengger Deserts (middle region [MR]), and Otindag Sandy Land (eastern region [ER]). We analyzed daily dust storm frequency (DSF) at the 10-day scale (first [FTDM], middle [MTDM], and last [LTDM] 10 days of a month), and investigated the association of dust storm occurrences with meteorological factors. The 10-day DSF was greatest in the FTDM (accounting for 77.14% of monthly occurrences) in the WR, MTDM (45.85%) in the MR, and LTDM (72.12%) in the ER, showing a clear trend of movement from the WR to the ER. Temporal analysis of DSF revealed trend changes over time at annual and 10-day scales, with mutation points at 1985 and 2000. We applied single-factor and multiple-factor analyses to explore the driving mechanisms of DSF at the 10-day scale. Among single factors, a low wind-speed threshold, high solar radiation, and high evaporation were correlated with a high DSF, effectively explaining the variations in DSF at the 10-day scale; however, temperature, relative humidity, and precipitation poorly explained variations in DSF. Similarly, multiple-factor analysis using a classification and regression tree revealed that maximum wind speed was a major influencing factor of dust storm occurrence at the 10-day scale, followed by relative humidity, evaporation, and solar radiation; temperature and precipitation had weak influences. These findings help clarify the mechanisms of dust storm occurrence in East Asia.

A comprehensive review of climate change impacts, adaptation, and mitigation on environmental and natural calamities in Pakistan

The devastations and damages caused by climate change are apparent across the globe, specifically in the South Asian region where vulnerabilities to climate change among residents are high and climate change adaptation and mitigation awareness are extremely low. Pakistan's low adaptive capacity due to high poverty rate, limited financial resources and shortage of physical resources, and continual extreme climatic events including varying temperature, continual flooding, melting glaciers, saturation of lakes, earthquakes, hurricanes, storms, avalanches, droughts, scarcity of water, pest diseases, human healthcare issues, and seasonal and lifestyle changes have persistently threatened the ecosystem, biodiversity, human communities, animal habitations, forests, lands, and oceans with a potential to cause further damages in the future. The likely effect of climate change on common residents of Pakistan with comparison to the world and their per capita impact of climate change are terribly high with local animal species such as lions, vultures, dolphins, and tortoise facing extinction regardless of generating and contributing diminutively to global GHG emissions. The findings of the review suggested that GHG emissions cause climate change which has impacted agriculture livestock and forestry, weather trends and patterns, food water and energy security, and society of Pakistan. This review is a sectorial evaluation of climate change mitigation and adaption approaches in Pakistan in the aforementioned sectors and its economic costs which were identified to be between 7 to 14 billion USD per annum. The research suggested that governmental interference is essential for sustainable development of the country through strict accountability of resources and regulation implemented in the past for generating state-of-the-art climate policy.

Impact of market misallocations on green TFP: evidence from countries along the Belt and Road

Based on the idea of a "Community of Human Destiny," the Chinese government proposed the "Belt and Road" initiative, and clearly proposed to promote green development and strengthen ecological environmental protection. However, a considerable number of countries are resource-rich economies with serious market misallocations. Using the stochastic frontier analysis (SFA) combined with the directional distance function (DDF) framework, this paper measures the green total factor productivity (GTFP) and its items (i.e., technical change and efficiency change) of 33 countries along the Belt and Road in 1995-2012, and then the impact of market misallocations on GTFP is analyzed. The following conclusions are drawn: (1) The main driving force for GTFP promotion in Asian countries came from technical change, while in European countries, it came from efficiency change. (2) Market misallocations had significantly hindered the GTFP of these economies. Countries with greater market misallocations have smaller GTFP. (3) Results based on counterfactual measures showed that GTFP could be increased by up to 4.04% and the average can be increased by 1.24% after eliminating market misallocations.

Divisional disparities on climate change adaptation and mitigation in Punjab, Pakistan: local perceptions, vulnerabilities, and policy implications

Climate change is a global challenge faced by everyone, but the developing countries are highly vulnerable to variations in the environment. This research focuses on the Punjab province of Pakistan and evaluates the impacts and consequences of climate change on general public at local and divisional level. In order to cope with the impacts of climatic changes at all levels, especially divisional level, raising reliable awareness and dispersing actionable knowledge regarding mitigating and adapting measures is significantly important. Therefore, recognition of information gaps, improvements in the level of alertness, and development of preventive measures in each sector is imperative. The impacts of climate change are observed across the country through gradual increase in temperature, human health issues, pest diseases, droughts, floods, and irregular weather patterns leading to changes in lifestyles, and these issues are likely to continue in the future. The main cause of climate change in Punjab, Pakistan, can be attributed to excessive release of greenhouse gases (GHG) into the atmosphere due to human activities involving inefficient energy usage, rapid urban expansion, improper waste management, industrial development, increasing transportation, agricultural activities, and livestock mismanagement. The findings of this study revealed that transportation sector is the major source of GHG emissions in the country, followed by industrialization and waste, at national, as well as divisional, level. The extent of impacts of climate change at divisional level is distinguishable and displayed a direct relationship with climate, geography, variation of effects, and modes of production in various regions of Punjab. The study strategically investigated all nine divisions of the province for comprehensive understanding of climate change phenomenon, and the results indicated that nearly three-fourths of the respondents have never indulged in taking steps towards climate change mitigation and adaptation. The study adopted a mixed (qualitative and quantitative) approach where the findings can act as set of guidelines for governmental authorities in formulating, assisting in preparation, instructing, and guiding policies for climate change mitigation and adaptation at national, local, and divisional levels. Graphical abstract.

Assessing the Vulnerabilities of Current and Future Production Systems in Punjab, Pakistan

Mankind is in peril and there are many reasons for this; however, climate change precedes all other reasons. Problems of poor farming communities are augmented due to the menace of climate change. This study endeavors to determine the effect on farming communities of both climate change and a situation without climate change. To carry out the study, three different districts were selected (Rawalpindi, Chakwal, and Layyah). Impact of the climate vagaries on per capita income, farm returns, and poverty of the respondents was taken into consideration. To achieve pathways analysis, regional representative agricultural pathways were used. The decision support system for agrotechnology transfer (DSSAT) crop growth model was employed for wheat-related simulations. The tradeoff analysis model for multidimensional impact assessment (TOA-MD) model was used for economic analysis. The results lend credence to the aforementioned nuisance of climate change, as the findings which came through were negatively affecting farm returns, per capita income, and poverty of the farmers. The negative impact applies to both current and future production systems. Farmers are up against the wall because of climate change and they will have to adopt new innovations to raise their productivity.

Linking Social Perception and Provision of Ecosystem Services in a Sprawling Urban Landscape: A Case Study of Multan, Pakistan

Urban sprawl causes changes in land use and a decline in many ecosystem services. Understanding the spatial patterns of sprawl and exploration of citizens’ perception towards the sporadic urban expansion and its impacts on an ecosystem to deliver services can help to guide land use planning and the conservation of the urban ecosystem. Here, we spatially examined land use changes in Multan, Pakistan, and investigated public perception about urban sprawl and its impacts on the quality and provision of ecosystem services, using a survey instrument. The spatial analysis of the historical land cover of Multan indicated an exponential expansion of the city in the last decade. Large areas of natural vegetation and agricultural land were converted to urban settlements in the past two decades. The citizens of Multan believe that the quality and provision of ecosystem services have declined in the recent past and strongly correlate the deteriorating ecosystem services with urban sprawl. Education and income levels of the respondents are the strongest predictors of urban ecosystem health literacy. Citizens associated with laborious outdoor jobs are more sensitive to the changes in ecosystem services. We concluded that the rapidly expanding cities, especially in the tropical arid zones, need to be prioritized for an increase in vegetation cover, and economically vulnerable settlements in these cities should be emphasized in climate change mitigation campaigns.

Future precipitation changes over China under 1.5 °C and 2.0 °C global warming targets by using CORDEX regional climate models

This study aims to characterize future changes in precipitation extremes over China based on regional climate models (RCMs) participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia project. The results of five RCMs involved in CORDEX-East Asia project that driven by HadGEM2-AO are compared with the simulation of CMA-RegCM driven by BCC-CSM1.1. Eleven precipitation extreme indices that developed by the Expert Team on Climate Change Detection and Indices are employed to evaluate precipitation extreme changes over China. Generally, RCMs can reproduce their spatiotemporal characteristics over China in comparison with observations. For future climate projections, RCMs indicate that both the occurrence and intensity of precipitation extremes in most regions of China will increase when the global temperature increases by 1.5/2.0 °C. The yearly maximum five-day precipitation (RX5D) averaged over China is reported to increase by 4.4% via the CMA-RegCM under the 1.5 °C warming in comparison with the baseline period (1986-2005); however, a relatively large increase of 11.1% is reported by the multi-model ensemble median (MME) when using the other five models. Furthermore, the reoccurring risks of precipitation extremes over most regions of China will further increase due to the additional 0.5 °C warming. For example, RX5D will further increase by approximately 8.9% over NWC, 3.8% over NC, 2.3% over SC, and approximately 1.0% over China. Extremes, such as the historical 20-year return period event of yearly maximum one-day precipitation (RX1D) and RX5D, will become more frequent, with occurrences happening once every 8.8 years (RX1D) and 11.5 years (RX5D) under the 1.5 °C warming target, and there will be two fewer years due to the additional 0.5 °C warming. In addition, the intensity of these events will increase by approximately 9.2% (8.5%) under the 1.5 °C warming target and 12.6% (11.0%) under the 2.0 °C warming target for RX1D (RX5D).

Integrated climate change risk assessment and evaluation of adaptation perspective in southern Punjab, Pakistan

Climate change is posing stresses on water resources, food security, population, environment and economy of the southern Punjab. Integrated climate change risk assessment is carried out using assessed likelihood approach for defined mean, hot & dry, central, warm & wet climate models over selected time slices and adaptation plans. Climate models are based on the 5^th, 50^th & 95^th percentiles of PRECIS RCM projections of temperature & precipitation under IPCC A2 & A1B scenarios. Four time slices 2015, 2035, 2065 and 2085 are selected to assess the temporal climate change risk and to evaluate the performance of selected adaptations to reduce climate threats over considered assets. Results are presented in terms of risk indices and risk reduction units (RRUs). In first half of the 21^st century, climate change risk will continue to increase from current level and is high (>10) in most of the selected time slices. Maximum ensembles of climate models, time slices and adaptation plans observe moderate (37-40 RRUs) and high (40-55 RRUs) risk class. Cumulative risk has been calculated through integration of sectoral sensitivity e.g. population density, land use, food security and multidimensional poverty to climate change risk class using AHP and overlaying in GIS environment. About 90% and 83% area of southern Punjab is falling in high cumulative risk. About 13% area, comprising Muzaffargarh and Rajanpur district is under very high cumulative risk. Water induced adaptations like development of water resources, dam & flood control protection, temporary flood barriers and water resource acquisition are the preferred and suitable adaptations as these observed >100 RRUs for most of the ensembles. Assessing baseline vulnerability and sectoral sensitivity to climate stimuli are the hot spots requiring priority attention and firm decision making by disaster management authorities and communities residing in southern Punjab.