Simulation of the interaction between an urban drainage system (UDS) and surface flow is a challenging issue. Conventional rainfall–runoff models are only able to simulate the flow in UDSs without considering the interaction between surface runoff and UDS. In this study, SWMM (storm water management model), as a well‐known urban drainage simulation model, and a two‐dimensional overland flow model developed based on the cellular automata approach, have been coupled for UDS simulation. In the proposed model, sewer flows are one‐dimensionally simulated using the SWMM model and at the flooded manholes, the surcharge hydrographs are determined. Then the two‐dimensional overland flow model is used for routing the surcharged flows. The coupled model could consider the complex interaction between the drainage system and the overland flow. The proposed model has been used in a study area located in Tehran, capital of Iran. The results show that almost 40% of surcharged flow returns back to the UDS, which caused 1.5% increase in the UDS's outflow volume. This can greatly affect the UDS performance downstream of the study area. The implementation results show the model's capability in simulation of flood behaviour as well as the urban inundated area with acceptable accuracy and much less computational effort. Copyright © 2017 John Wiley & Sons, Ltd.

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<p><span class="TextRun Highlight SCXW95865197 BCX9" lang="EN-US" xml:lang="EN-US" data-contrast="none"><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun" data-ccp-charstyle-defn="{"ObjectId":"3c7fb4e2-e3a3-4ada-9a15-ac425120260c5","ClassId":1073872969,"Properties":[469775450,"normaltextrun",201340122,"1",134233614,"true",469778129,"normaltextrun",335572020,"1",469778324,"Default Paragraph Font"]}">ITHACA is a 5-year project that aims </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">to</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> benchmark the terrestrial water cycle intensification. </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">Our goal is to</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> estimate the past range of </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">the </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">hydrological cycle variability, </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">determine</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> the present state of its acceleration, and understand its future impacts on </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">the </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">terrestrial water availability.</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> To achieve this, we </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">combin</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">e</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> multi-</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">source data products, stochastic</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> analysis,</span> <span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">and </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">process-based hydrological modeling</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> from regional to global scale</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">.</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> Here, we present the preliminary results a</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">fter the completion of its first year</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">, which come with multiple homogenized datasets of water cycle components, R </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">software </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">packages for data pre-processing and data-driven analyses, and methodological suggestions and insights</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> for the cross-scale quantification of water cycle changes</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">. </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">We also discuss the current challenges and the future steps of the project, highlighting the </span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun">numerous</span><span class="NormalTextRun SCXW95865197 BCX9" data-ccp-charstyle="normaltextrun"> opportunities for active collaboration. </span></span><span class="EOP SCXW95865197 BCX9" data-ccp-props="{"201341983":0,"335559739":160,"335559740":259}"> </span></p>

<p><span xml:lang="EN-US" data-contrast="auto"><span>The Mediterranean has been characterized as a region of enhanced climatic variability. Transitions between dry and wet conditions have repeatedly occurred over the last millennium in various spatial and temporal scales. However, the frequency of these shifts is poorly assessed due to the low amount of paleoclimatic reconstructions and the substantial heterogeneity of the Mediterranean. Here, we examine how often Mediterranean regions have transitioned between different hydroclimatic regimes over the last millennium. For this purpose, we use the Paleo Hydrodynamics Data Assimilation (PHYDA) simulation results to </span><span>i</span><span>dentify</span> <span>transitional changes based on Köppen-Geiger climate types. Our results </span><span>i</span><span>ndicate</span> <span>which regions are more likely to experience transitions between hydroclimatic regimes and their duration distribution. We also examine how the intensity of the shifts have fluctuated during the study period and quantify the uncertainties involved. Our findings contribute to a better understanding of the past hydroclimatic variability, which is crucial for further </span><span>d</span><span>etermining</span> <span>the current state and future aridification in the Mediterranean region. </span></span><span> </span></p>