The project management system has many tools and techniques to control projects' main elements schedule, cost, quality, risk, communications and procurements to attain project success and high performance. Earned value analysis (EVA) is the most effective tool to measure project performance which is widely used by many organisations such as Defence Acquisition University; National Aeronautics and Space Administration; Society of Cost Estimates and Analysis; and Project Management Institute (PMI)  to measure project performance and control it through cost and schedule,  which are illustrated into graphs to forecast the project results to be shared and reported to top management, stakeholders and client in regular basis taking into consideration the other factors such as risk management, project environment, quality, safety, control charts, and sustainability to attain highly performance. Proposed methodology in the presented paper to implement the integrated EVA in an effective and uncomplicated way to attain project success and high performance using an automated sheet to perform analysis for an anonymous hospital design project with the total duration of seven months and illustrates and summarises the key factors based on previous studies and project examples.

Flash flooding risk impacts can be reduced through the implementation of mitigation strategies plan (MSP) for flood management. This study aims to develop a flash-floods risk mitigation plan, which appears to be beneficial for municipalities, provincial administrators, and authorities to reduce the impact of the flash flood in the Kyrenia region, Northern Cyprus. In this work, rainfall data were collected from the nearest stations for 22 years. The return periods of maximum daily rainfall are also determined by using six formulas. Furthermore, flood inundation and hazard maps were defined by utilizing SAGA, QGIS, ArcGIS, 2D HEC RAS, and HEC -HMS software then determining the degree of risk and identifying strategies based on quantitative risk analysis by developing a risk matrix. As a final result, catastrophic risk areas are distributed significantly downstream. In conclusion, the proposed flash flood mitigation plan includes strategies to reduce flood losses of human life and constructed structures across Kyrenia and proposed hazard and inundation risk maps to assess planners and decision-makers for the potential impact of floods to avoid.   Keywords: DEM; Flash Flood; Hazard map; HEC-RA Mitigation plan; Risk matrix

Girne region is in the northern part of Northern Cyprus which is environmentally fragile and susceptible to natural disasters. Flash floods are a major problem in the region due to the heavy and torrential rainfalls in its urban environment. Therefore, this study aims to assess the flash flood risk for the Girne region, using the Geographic Information System (GIS). A mitigation flood risk plan is proposed and applied to the case study of the Girne region. The flood risk matrix is proposed based on the occurrence probability of the flood and the associated inundation depth. The risk matrix criterion was classified according to the degree of risks as high, moderate, and low. Five thematic maps affecting flood occurrences, including slope, elevation, land use, peak discharge, and flow accumulation, were classified to generate flood hazard maps. The results of the estimation of the magnitude of the inundation areas that can assess the degree of damage and its economic aspects are presented graphically. The developed flood risk matrix tool is a quantitative tool to assess damage and is essential for decision-makers.

The consistency of hydrological process modeling depends on reliable parameters and available long-term gauge data, which are frequently restricted within the Dead Sea/Jordan regions. This paper proposes a novel method of utilizing six satellite-based and reanalysis precipitation datasets, which are assessed, evaluated, and corrected, particularly for the cases of ungauged basins and poorly monitored regions, for the first time. Due to natural processes, catchments fluctuate dramatically annually and seasonally, making this a challenge. This variability, which is significantly impacted by topo-geomorphological and climatic variables within the basins themselves, leads to increased uncertainty in models and significant restrictions in terms of runoff forecasting. However, quality evaluations and bias corrections should be conducted before the application of satellite data. Moreover, the hydrological HEC-HMS model was utilized to predict the runoff under different loss methods. Furthermore, this loss method was used with an integrated model that might be efficiently employed when designing hydraulic structures requiring high reliability in predicting peak flows. The models’ performance was evaluated using R-squared (R2), the root mean square error (RMSE), the mean absolute error (MAE), and Nash–Sutcliffe efficiency (NSE). In addition, these statistical metrics were implemented to quantitatively evaluate the data quality based on the observed data collected between 2015 and 2020. The results show that AgERA5 exhibited better agreement with the gauge precipitation data than other reanalysis precipitation and satellite-based datasets. The results demonstrate that the data quality of these products could be affected by observational bias, the spatial scale, and the retrieval method. Moreover, the SC loss method demonstrated satisfactory values for the R2, RMSE, NSE, and bias compared to the IC and GA loss, indicating its effectiveness in predicting peak flows and designing hydraulic structures that require high reliability. Overall, the study suggests that AgERA5 can provide better precipitation estimates for hydrological modeling in the Dead Sea region in Jordan. Moreover, integrating the SC, IC, and GA loss methods in hydraulic structure design can enhance prediction accuracy and reliability.

Kyrenia region is in the northern part of Northern Cyprus that is environmentally fragile and susceptible to natural disasters. Thus, the study of frequency analysis is essential to find the most suitable model that could detect the region’s risk in certain natural phenomena such as rainfall, flood, and so on. The objective of this research is to determine the best fit probability distribution in the case of average daily rainfall and total rainfall using 22 years of data (1995-2016) from the Kyrenia region in Northern Cyprus by using 37 probability distribution models. The best-fit probability distribution in the case of maximum annual daily rainfall is determined using various distribution types. Three goodness-of-fit test statistics were applied. Beta, Dagum, Wakeby, Paretoa, Log-Pearson 3, Gen. Extreme Value, and Gen. Gamma (4P) showed the largest number of best-fit results. The results of this study can be used to develop more accurate models of flooding risk and damage.   Keywords: Distribution function; goodness-of-fit tests;  Northern Cyprus; rainfall.