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Flood mapping is a vital component for sustainable land use in flood-prone areas. Due to the frequency of flood events, local authorities demand effective yet simple methods for the preliminary identification of flood-prone areas at large scales to subsequently define mitigation strategies. We focus here on the workflow GeoFlood, a parsimonious model which uses only high-resolution Digital Terrain Models (DTMs) to define the geomorphological and hydrological information necessary for flood inundation mapping, thus allowing for large-scale simulations at a reasonable computational cost. The purpose of the present study is to investigate the conditions under which GeoFlood is able to correctly reproduce inundation scenarios (with an assigned return period) and their flooding characteristics. Specifically, we analyze its performance over a highly urbanized area, the mid-lower portion of the Tiber River (Italy). We

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We compare inundation estimates with high-water marks collected during Hurricane Harvey. Our system estimates depth with a 0.5-m mean error and extent covering 90% of that obtained from observations. ABSTRACT: Flood modeling provides inundation estimates and improves disaster preparedness and response. Recent development in hydrologic modeling and inundation mapping enables the creation of such estimates in near real time. To quantify their performance, these estimates need to be compared to measurements collected during historical events. We present an application of a flood mapping system based on the National Water Model and the Height Above Nearest Drainage method to Hurricane Harvey. The outputs are validated with high-water marks collected to record the highest water levels during the flood. We use these points to compute elevation-related variables and flood extents and measure the quality of the estimates. To improve the performance of the method, we calibrate the roughness coefficient based on stream order. We also use lidar data with a workflow named GeoFlood and we compare the modeled inundation to that recorded by the high-water marks and to the maximum inundation extent provided by the Dartmouth Flood Observatory based on remotely sensed data from multiple sources. The results show that our mapping system estimates local water depth with a mean error of about 0.5 m and that the inundation extent covers over 90% of that derived from high-water marks. Using a calibrated roughness coefficient and lidar data reduces the mean error in flood depth but does not affect as much the inundation extent estimation.

<p>Land use and delineation of flood-prone areas require valuable and effective tools, such as flood mapping. Local authorities, in order to prevent and mitigate the effects of flood events, need simplified methodologies for the definition of preliminary flooded areas at a large scale. In this work, we focus on the workflow GeoFlood, which can rapidly convert real-time and forecasted river flow conditions into flooding maps. It is built upon two methodologies, GeoNet and the HAND model, making use only of high-resolution DTMs to define the geomorphological and hydraulic information necessary for flood inundation mapping, thus allowing for large-scale simulations at a reasonable economical and computational cost. GeoFlood potential is tested over the mid-lower portion of the river Tiber (Italy), investigating the conditions under which it is able to reproduce successful inundation extent, considering a 200-year return period scenario. Results are compared to authority maps obtained through standard detailed hydrodynamic approaches. In order to analyze the influence of the main parameters involved, such as DTM resolution, channel segmentation length, and roughness coefficient, a sensitivity analysis is performed. GeoFlood proved to produce efficient and robust results, obtaining a slight over-estimation comparable to that provided by standard costly methods. It is a valid and relatively inexpensive framework for inundation mapping over large scales, considering all the uncertainties involved in any mapping procedure. Also, it can be useful for a preliminary delineation of regions where the investigation based on detailed hydrodynamic models is required.</p>

<p>Open-loop shallow geothermal systems, which exploit shallow aquifers as a heat source or sink, have a great potential to reduce greenhouse gas emissions related to the heating and cooling of buildings. In order to limit the depletion of groundwater resources water is generally reinjected into the same aquifer after the heat exchange, as a consequence a thermal plume develops within the aquifer. Furthermore a share of the reinjected water may come back to the abstraction wells, inducing a progressive thermal alteration of the abstracted water temperature that may even result in the plant failure. This phenomenon, known as thermal recycling, strongly depends on the hydraulic conductivity of the aquifer. The design models commonly adopted in the practice assume a homogeneous domain with constant hydraulic conductivity, this assumption, however, is not realistic: neglecting the natural heterogeneity of hydraulic properties of the porous medium may result in large prediction errors.</p><p>In this study, we aim to quantify the impact of the different heat transport dynamics in aquifers on the thermal plume development. A stochastic model, which explicitly considers the spatial variability of the hydrological properties, such as the hydraulic conductivity, is developed for low enthalpy geothermal systems. The thermal breakthrough curve at the extraction well is obtained by applying a Lagrangian model and assuming a steady state velocity field. Relevant quantities of thermal recycling, such as the thermal breakthrough time, are adopted for the evaluation of the effects of the hydrogeological and geometrical parameters of the systems.</p><p>The results of our study emphasize how the correct representation of the aquifer heterogeneity is fundamental in the design of shallow geothermal systems and in the correct heat plume assessment.</p>

<p>Shallow geothermal systems represent a unique opportunity for heating and cooling of buildings with green energy and low operational costs.</p><p>Efficiency of  geothermal system is strictly related to the local subsurface flow field that moves water and energy; given the great spatial variability of hydrological and thermal properties in the subsurface environment a reliable assessment of the geothermal system efficiency requires a probabilistic approach that takes into account the uncertainty on the predictions. </p><p>Homogeneous domain and purely advective flow are typical hypotheses currently adopted in the design of geothermal systems, the aim of our research is to investigate how the variability of thermo-hydrological and engineering parameters impact the different heat transport dynamics and how they result in the GS efficiency.</p><p>The study adopt a Lagrangian description of the heat transport based on the travel time evaluation.</p><p>As application example we consider an open loop system made by a well doublet placed into a confined heterogeneous aquifer of constant thickness.</p><p>The efficiency of the system is evaluated considering lumped parameters, usually adopted in the GS deign, such as the water recirculation ratio or the first breakthrough time and introducing more effective descriptors such as the total breakthrough time curve or the temperature evolution at the abstraction well.</p><p>The analysis suggests that the first breakthrough time, the key parameter adopted in the GS design, decreases with heterogeneity, furthermore, the uncertainty associated with early arrivals increases with heterogeneity. Medium heterogeneity, on the other hand, has a very small impact on the recirculation ratio and on the long-term period, while the pumping rate and other geometrical parameters have a strong impact on its value.</p><p>Since well screens usually cross a short depth we perform a detailed analysis on the uncertainty related to the ergodicity issue. Results of a single realization can significantly differ from its ergodic counterpart. As a practical consequence, a thermal feedback occurring in a heterogeneous medium could significantly differ from the expected theoretical one.</p>

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