Impact of a Non-Dedicated U-Turn on Traffic

Non-dedicated U turn has a direct effect on road safety, capacity and congestion during the traffic flow. U turn can have significant supremacy on traffic flow and headway. Therefore to study the impact of non-dedicated u turns on traffic is the ultimate requirement of the current time. This is a microscopic traffic study in which the data from a U turn (33°59’48.2"N 71°27’30.2"E) on road leading to Hayatabad and Karkhano in Peshawar is evaluated in terms of headway, speed and flow rate of traffic. Factual data is presented which shows that the average time headway surges when the traffic is interfered by the U turning vehicles. The probability density functions and cumulative density functions fit to the datasets of headway are then evaluated by the techniques of anova analysis to determine which distribution is the most suitable one for the data. Distribution data specific with the interfering U turn was taken in a separate set and evaluated. The result obtained show that the Burr Distribution and Generalized Extreme Value Distribution are the optimum to illustrate the headway data of traffic being interfered by U turning vehicles. This ligitimize the utilization of various time headway distributions of vehicles being interfered by U turning for traffic modeling.

Evaluation of Impact of Climate Change on Pakistans Agriculture: Spatial and Temporal Analysis

The most crucial challenge in 21st century is the threat to agriculture sector through global climate changes. It has caused a significant impact on water and energy resources, agriculture sector and consequently food supply especially for developing countries. Pakistan is the frontline state confronting the serious concerns of climate change particularly grave water shortage. Its economy has been facing the challenges of global warming, devastating floods, persistent droughts, rising sea levels etc. Keeping in view extreme vulnerability to climate change, a comprehensive economic valuation was quantified across time and region so as to bring some workable policy solutions for the agrarian economy of this country. The present study consists of multifaceted approach including desk review of national policies of Pakistan falling within the purview of agriculture and climate change, mapping international and national reviews of climate change impacts on agriculture sector, assessment of extreme climate events, technical ranking of agro-climatic zones in accordance with farmers’ vulnerability to climate change and drought situation and lastly, assemblage and analysis of climate and agriculture data to develop climate change-agriculture linkages. A comprehensive meta-analysis of available literature for Ricardian studies revealed that 1°C increase in temperature decreased world farm land values by 1585 USD per hectare and 1mm increase in rainfall increased world farm land values by 69 USD per hectare while net climate change impact on farm land was negative where unit change in climate decreased farm land values about 614 USD per hectare. At continent level, climate changes were found to be blessings for Europe and America while Asia was found as the most vulnerable continent to climate change besides Africa that is also facing vulnerability to climate change. Funnel asymmetry plot and FAT showed that literature was free of publication bias and heterogeneity. Likewise PET showed negative effect of climate change on farm land values. The study also investigated the extreme climate events including flood zone, drought trends and severity. The cotton-wheat Sindh was most drought prone zone followed by rice-other Sindh, other Balochistan and cotton-wheat Punjab. The interpolated drought index assessed Chagai, Kharan, Panjgur, Kech, Gawadar and Awaran from Balochistan and Jacobabad, Shikarpur, Sakhar, Larkana, Nowshehro Feroz, Nawab Shah, Dadu and Khairpur from Sindh most susceptible to drought. The estimated farmers’ vulnerability to climate change showed that farmers of Khyber Pakhtun Khwah were most vulnerable to climate while farmers from other Balochistan and low intensity Punjab were also found to be at stake. While farmers from mixed Punjab and rice-wheat Sindh are least vulnerable to climate change. Spatial clustering in climate response function provides the evidence to add in the spatial impact in Ricardian studies. Furthermore, the interpolated climate normal were used in the study due to available climate data dearth. Ricardian estimates showed that 1 °C increase in temperature will decrease net farm revenues by 739 Rupees while 1 mm increase in rainfall will increase the net farm revenues by 10 rupees. Since the net climate change effect is 729 rupees per hectare. The optimal minimum temperature is 17.45 °C, optimal maximum temperature is 32 °C and optimal rainfall level is 250 mm for Pakistan. Climate response to net farm revenues in irrigated regions was estimated by loss of 6586 Rupees for irrigated and 117 Rupees in rainfed region indicating that irrigated region is more vulnerable to climate change in comparison to rainfed region. Threshold level of minimum temperature in rainfed is 18 C and in irrigated region is 20 C while optimal precipitation level in rainfed is 626 mm and in irrigated regions is 958 mm. farm type adaptation to climate change estimated through logistic regression proposed that for increased temperature, the irrigated farmers will prefer crop only farming and rainfed farmers will prefer mixed farming. However, the precipitation increase will attract farmers towards mixed farming in both regions. This all research endeavor showed the overall negative impact of climate change to agriculture sector in Pakistan particularly in districts of Rahim Yar Khan, Bahawalpur, Narowal and Chiniot from Punjab, Zhob, Sibbi, Ziarat and Quetta from Balochistan, Chitral, Dir, Swat and Batgram from Khyber Pakhtun Khwah. Since farm type adaptations, use of good quality seed, and efficient agriculture extension services can reduce the vulnerability of agriculture sector to climate change to proceed towards sustainable development. The findings in this study would be a comprehensive addition in the existing body of literature that, on one hand, would help the researchers to continue exploring the new dimensions of research with advanced econometric techniques and on the other hand, help the policy experts to frame workable strategies for agrarian economy of Pakistan under unfriendly climate scenario.