RESUMEN
Digital Elevation Models (DEMs) play a significant role in hydraulic modeling and flood risk management. This study initially investigated the effect of Unmanned Aerial Vehicle (UAV) DEM resolutions, ranging from 1 m to 30 m, on flood characteristics, including the inundation area, mean flow depth, and mean flow velocity. Then, the errors of flood characteristics for global DEMs, comprising ALOS (30 m), ASTER (30 m), SRTM (30 m), and TDX (12 m) were quantified using UAV DEM measurements. For these purposes, the HEC-RAS 2D model in steady-state conditions was used to simulate the flood with return periods of 5- to 200 years along 20 km reach of Atrak River located in northeastern Iran. Results indicated when UAV DEM resolution decreased from 1 m to 30 m, inundation area and mean flow depth increased 17.0% (R2 = 0.94) and 10.2% (R2 = 0.96) respectively, while mean flow velocity decreased 16.8% (R2 = -0.94). Validation of the hydraulic modeling using the modified normalized difference water index demonstrated that the HEC-RAS 2D model in conjunction with UAV DEM simulates the flood with â92% accuracy. Comparing the global DEMs with UAV DEM showed that the root mean square error (RMSE) values of the flow depth for ASTER, SRTM, ALOS, and TDX DEMs were 1.77, 1.12, 1.02, and 0.93 m, and the RMSE values of the flow velocity for the same DEMs were 0.81, 0.66, 0.55, and 0.47 m/s, respectively. Furthermore, TDX DEM with a 6.15% error in the inundation area was the nearest to UAV measurements. Overall, TDX DEM revealed a better performance in hydraulic modeling of the fluvial flood characteristics. Hence, it is recommended for environments where high-resolution topography data is scarce. The results of this study could potentially serve as a guideline for selecting global DEMs for hydraulic simulations.
RESUMEN
The estimation of long-term groundwater recharge rate ([Formula: see text]) is a pre-requisite for efficient management of groundwater resources, especially for arid and semi-arid regions. Precise estimation of [Formula: see text] is probably the most difficult factor of all measurements in the evaluation of GW resources, particularly in semi-arid regions in which the recharge rate is typically small and/or regions with scarce hydrogeological data. The main objective of this study is to find and assess the predicting factors of [Formula: see text] at an aquifer scale. For this purpose, 325 Iran's phreatic aquifers (61% of Iran's aquifers) were selected based on the data availability and the effect of eight predicting factors were assessed on [Formula: see text] estimation. The predicting factors considered include Normalized Difference Vegetation Index (NDVI), mean annual temperature ([Formula: see text]), the ratio of precipitation to potential evapotranspiration ([Formula: see text]), drainage density ([Formula: see text]), mean annual specific discharge ([Formula: see text]), Mean Slope ([Formula: see text]), Soil Moisture ([Formula: see text]), and population density ([Formula: see text]). The local and global Moran's I index, geographically weighted regression (GWR), and two-step cluster analysis served to support the spatial analysis of the results. The eight predicting factors considered are positively correlated to [Formula: see text] and the NDVI has the greatest influence followed by the [Formula: see text] and [Formula: see text]. In the regression model, NDVI solely explained 71% of the variation in [Formula: see text], while other drivers have only a minor modification (3.6%). The results of this study provide new insight into the complex interrelationship between [Formula: see text] and vegetation density indicated by the NDVI. The findings of this study can help in better estimation of [Formula: see text] especially for the phreatic aquifers that the hydrogeological ground-data requisite for establishing models are scarce.
RESUMEN
Assessing environmentally sustainable GW management (ESGM) needs a deep knowledge of the present and the projected status of GW (GW) quantity and quality. Translations of these data into policy relevant information are usually done through quantitative indices. Despite the availability of a dozen GW sustainability indicators, defining an integrated index based on internationally accepted scientific standards indicators is required. To fill this gap, an in-depth review on the developed indicators/index for evaluation of GW sustainable management (GWSM) from an environmental viewpoint at aquifer scales is provided in this study. Thirteen environmentally related quantitative indicators are adopted for assessment of GWSM, especially in arid regions, depending upon data availability, and relevance of indicators. An integrated ESGM index (ESGMI) is developed based on weighted aggregation of thirteen adopted indicators through multi criteria decision making (MCDM) methods. ESGMI value ranged between 0 and 100, zero value denotes to the worst state or unsustainable GW management (GWM) and 100 indicates the ideal state or GWM is sustainable. Thirty important aquifers across Iran are chosen to implement the ESGMI at the national scale of a country known to be the fifth largest global GW user. ESGMI values for thirty of Iran's aquifers are obtained in the range 15.40 to 68.50 (on average, 49.96). This reveals the unsustainable status of GWM in this country. The results of this study demonstrate that the ESGMI is a promising tool to determine the current state of GW quantity and quality, reveals the effect of policy actions and plans, and contributes to the development and operation of effective sustainable management policies for GW resources. Due to uncertainties and spatio-temporal variabilities of key controlling variables in GW management, sustainability evaluation should be understood as a dynamic and iterative process, requiring persistent monitoring, analysis, prioritization, and modification.
