Optimization of Monitoring Network to the Rainfall Distribution by Using Stochastic Search Algorithms: Lesson from Pakistan

Abstract

Agricultural production is greatly influenced by environmental parameters such as temperature, rainfall, humidity, and wind speed. The accurate information about environmental parameters plays a vital and useful role when making policies for the agriculture sector as well as for other sectors. Pakistan meteorological department observed these environmental parameters at more than 90 stations. The allocation of these monitoring stations is not made systematically correct. This leads to inaccurate predictions for unobserved locations. The study aims to propose a monitoring network by which these prediction errors of the environmental parameters can be minimized. The well-known prediction techniques named, model-based ordinary kriging and model-based universal kriging (UK) with the known Matheron variogram model are used for prediction purposes. We investigate the monitoring network of Pakistan for rainfall and focus on both the optimal deletion/addition of monitoring stations from/to this network. The two stochastic search algorithms, spatial simulated annealing, and genetic algorithm are used for optimization purposes. Furthermore, the minimization of the Average Kriging Variance (AKV) is taken as the interpolation accuracy measure. The spatial simulated annealing exhibits a lower AKV as compared to the Genetic algorithm when adding/removing the optimal/redundant locations from the monitoring network.

The impact of environmental change on landslides, fatal landslides, and their triggers in Pakistan (2003–2019)

“…Prolonged rainfalls in the monsoon season bring along dangers with them as rains have been identified as a major trigger for triggering the landslides in general (Iverson 2000;Gariano and Guzzetti 2016). Heavy precipitation is the main trigger for the landslides in several of the studies done worldwide, and the case is similar in Pakistan as well, which sees its highest amount of rainfall in the Monsoon season (Keefer et al 1987;Gerrard and Gardner 2000;Naranjo 2007;Lazzari and Piccarreta 2018;Omer et al 2019Omer et al , 2022. A study on the effects of fatal landslides on the global scale also validates that the extreme rainfall is the major cause of landslides in more than half of the cases of landslides triggered by rainfall (Haque et al 2019).…”