Heat waves are occurring more frequently worldwide as global warming continues, and urban heat islands can threaten conventional life in cities. Measuring, analyzing, and simulating weather data at fine spatial and temporal scales are essential to prevent and reduce the damage caused by extreme heat waves. In urban environments, handling complex micrometeorological situations using current meteorological stations and global simulation models (e.g., weather research forecasting models) is challenging. In this study, the thermal environments of urban areas were measured using a mobile meteorological measurement platform. Both mobile and stationary datasets were incorporated into the meteorological modeling process to simulate the spatial and temporal distribution of temperature. Additionally, various mobile observation implementation scenarios for temperature modeling were examined. We compared simulation combinations with the temperature field generated from the total dataset to obtain a better sampling campaign and properly incorporate mobile data scenarios. When collecting mobile data, it is important to consider spatial features to improve the efficiency of sampling programs. This can substantially reduce the cost of mobile data collection, together with the sensor error bound.

The detection of small side branches within underground water pipe networks can be challenging since they are usually subject to many unknown uncertainties. A transient-based method was proposed to detect multi-branching pipes in pipeline systems having uncertainties associated with unknown abnormalities. To isolate the uncertainty signal from the original pressure signal, a polynomial transient model was developed that can address nonlinear transient introduction. Through the superimposition of different pressure signals, the uncertainty signal was delineated to obtain the processed signal for multi-branch prediction. Pipeline systems with two branching pipes were tested under various uncertainties to detect multi-branching pipes. In this study, two transient generation conditions were used: an instant valve closure and a pressure injection. Under several uncertainty conditions, hydraulic pressure damping can be obtained for the detection of two branching pipes under both transient generation conditions. It is possible to predict the locations of multi-branching pipes with a prediction error of less than 10% by using proper signal processing and manipulation for two distinct transient generation methods in a pilot-scale pipeline system with several uncertainties. This study demonstrates the potential for detecting multi-branching pipes in a pipeline system, even with unknown uncertainties for a pipeline system.

A water distribution system is an essential part of urban water management, as it ensures reliable water supply to residents. In order to monitor water distribution systems and prevent several problems, pressure sensors are an important part of the infrastructure, which should be examined frequently. The purpose of this study is to propose a method for evaluating pressure sensors in existing water distribution systems based on data analysis. Water distribution system in Yeonam District, Daegu Metropolitan City, was used in this study. We obtained field pressure data using a low accuracy field pressure sensor. Two different types of data were collected: daily data and high frequency data from transient events. Analyzing and evaluating field pressure data was based on information theory, which quantifies entropy as an indication of the amount of information in a signal. The best sampling frequency for a pressure sensor can be determined by determining data feasibility in transient data and the optimal sampling frequency for daily data.

Climate change frequently generated extreme meteorologic event. The temperature difference between urban and its adjacent rural area had been defined as Urban Heat Island(UHI). The UHI during nighttime associated with high humidity condition introduces inconvenient living condition during Monsoon season. The generation of rainfall event and intensity of UHI had been known to counter reciprocal due to the apparent rainfall disturbance to vertical temperature profile. The hydro-meteorological data collected during summer season between 2013 and 2022 was used to evaluate the UHI intensity in Busan, South Korea. The impact of rainfall generation pattern was analyzed to configure the relationship rainfall and nighttime UHI. The results were derived that the temperature difference showed the characteristics of each year rather than the regular form.

The managment of water distribution systems is important not only for reliable water conveyance considering water quality but also for effcient asset management of pipeline infrastructure. Abnormality detection is a critical issuefor pipeline management authorities. Unknown side branches and dead ends are detrimental to efficient pipeline operation. Hence, this sudy explores a general method for detecting multiple side branches in a pipeline system. The method of caracteristics was used to simulate the transient responses of a specific branch with or without branched elements. The isolated pressure response of each branch and the interference caused by different elements of the pipeline was subsequently identified. A nonlinear valve action maneuver was considered for water hammer generation using a polynominal equation during mathmatical modeling. Experimental pressure decay patterns for various pipeline structure combinations showed differences between the numerical model and real-life system, which were explained by unsteady friction. The detection and location of side branches was achieved by considering the phase pressure bounce for which the numerical and experiment results were consistent.