This study aims to conduct a thorough investigation to compare the abilities of quantile mapping (QM) techniques as a bias correction method for the raw outputs from general circulation model (GCM)/regional climate model (RCM) combinations. The Karkheh River basin in Iran was selected as a case study, due to its diverse topographic features, to test the performances of the bias correction methods under different conditions. The outputs of two GCM/RCM combinations (ICHEC and NOAA-ESM) were acquired from the coordinated regional climate downscaling experiment (CORDEX) dataset for this study. The results indicated that the performances of the QMs varied, depending on the transformation functions, parameter sets, and topographic conditions. In some cases, the QMs' adjustments even made the GCM/RCM combinations' raw outputs worse. The result of this study suggested that apart from DIST, PTF:scale, and SSPLIN, the rest of the considered QM methods can provide relatively improved results for both rainfall and temperature variables. It should be noted that, according to the results obtained from the diverse topographic conditions of the sub-basins, the empirical quantiles (QUANT) and robust empirical quantiles (RQUANT) methods proved to be excellent options to correct the bias of rainfall data, while all bias correction methods, with the notable exceptions of performed PTF:scale and SSPLIN, performed relatively well for the temperature variable.

Event hydrologic modeling reveals how a basin responds to an individual rainfall event (e.g., quantity of surface runoff, peak, timing of the peak, detention). In contrast, continuous hydrologic modeling synthesizes hydrologic processes and phenomena (i.e., synthetic responses of the basin to a number of rain events and their cumulative effects) over a longer time period that includes both wet and dry conditions. Thus, fine-scale event hydrologic modeling is particularly useful for understanding detailed hydrologic processes and identifying the relevant parameters that can be further used for coarse-scale continuous modeling, especially when long-term intensive monitoring data are not available or the data are incomplete. Joint event and continuous hydrologic modeling with the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is discussed in this technical note and an application to the Mona Lake watershed in west Michigan is presented. Specifically, four rainfall events were selected f...

Water resources in the Middle East region are becoming scarce, while millions of people already do not have access to adequate water for drinking and sanitary purposes. Water resources depletion has become a significant problem in this region that is likely to worsen. Current research by remote sensing analysis indicates a descending trend of water storage in the Middle East region, where agriculture plays a crucial role in socio-economic life. This study introduces an approach quantifying water depletion in the Middle Eastern countries, which are being challenged in the management of their water resources. Furthermore, this paper presents results of a survey assessing the status of water use and supply in Middle Eastern countries and outlines some potential remedies. Specifically, Iran's water use is evaluated and compared with its neighbors'. The water equivalent anomaly (WEA) and total water storage (TWS) depletion are two indexes of water scarcity calculated for Middle Eastern countries surveyed herein. Our analysis reveals that Lebanon, Syria, Iraq, and Iran are countries with very negative water scarcity indexes. These estimates prove that international cooperation is needed to manage available regional water resources and reverse depletion of natural water sources. It is demonstrated herein that virtual water trade can help remediate regional water shortage in Middle Eastern countries.