Land use/land cover change along the Eastern Coast of the UAE and its impact on flooding risk

This study was conducted to investigate the spatiotemporal changes of land use/land cover (LULC) along the eastern coast of the United Arab Emirates (UAE) over a 20-year period using an integration of remote sensing and Geographic Information Systems techniques. The impact of land use change on flooding potential was also investigated through hydrologic model simulations. Landsat images of the years 1996, 2006 and 2016 were processed and analyzed. Change detection was carried out to assess changes in the built-up areas. Furthermore, the impact of urbanization on flooding was assessed using a hydrologic model in two major watersheds of Fujairah Emirate. It was observed that for the period 1996–2006 the vegetation and the built-up areas had increased at a rate of 11.23% and 24.56%, respectively. For the period 2006–2016, this expansion more than doubled in terms of the vegetation class (27.51%) and slightly increased for the built-up class (28.98%). The change detection analysis revealed that urbanization has mostly occurred along the coastal boundary. Hydrologic model simulations quantified the role of urbanization in increasing the flooding potential. The increase depends on watershed characteristics and the rate of change in urbanization and the magnitude of the rainfall event

Spatio-Temporal Analysis of Precipitation Frequency in Texas Using High-Resolution Radar Products

Understanding the frequency and intensity of precipitation is needed for many vital applications including water supply for agricultural, municipal, industrial, and power generation uses, design of hydraulic structures, and analysis and forecasting of hazards such as flood, drought, and landslide. This study examines, in detail, the spatial and temporal variability of precipitation frequency over the State of Texas and its trends from 2002 to 2019. The results indicate that Texas receives around 325 wet hours on average annually (3.7% of the time). The northern part of the Gulf Coast region witnesses the highest average precipitation frequency reaching 876 wet hours annually. The year 2015 was found to have the highest precipitation frequency across the state with an average frequency of 6% (525 wet hours) and 2011 was the driest, with an average frequency of 1.9% (170 wet hours). In terms of seasonality, the highest precipitation frequency was observed in the summer with a frequency of 4.1%. The areal average time-series of the precipitation frequency indicates that the 2011–2012 drought to be a change point. The Mann–Kendall trend analysis shows that 16.2% of the state experienced a significant positive trend in precipitation frequency including the dry western region and major cities. The results can provide useful information about storm characteristics and recent change and variability of precipitation at high spatial resolutions and can be used in a multitude of practical applications

Development and Assessment of High-Resolution Radar-Based Precipitation Intensity-Duration-Curve (IDF) Curves for the State of Texas

Conventionally, in situ rainfall data are used to develop Intensity Duration Frequency (IDF) curves, which are one of the most effective tools for modeling the probability of the occurrence of extreme storm events at different timescales. The rapid recent technological advancements in precipitation sensing, and the finer spatio-temporal resolution of data have made the application of remotely sensed precipitation products more dominant in the field of hydrology. Some recent studies have discussed the potential of remote sensing products for developing IDF curves. This study employs a 19-year NEXRAD Stage-IV high-resolution radar data (2002–2020) to develop IDF curves over the entire state of Texas at a fine spatial resolution. The Annual Maximum Series (AMS) were fitted to four widely used theoretical Extreme Value statistical distributions. Gumble distribution, a unique scenario of the Generalized Extreme Values (GEV) family, was found to be the best model for more than 70% of the state’s area for all storm durations. Validation of the developed IDFs against the operational Atlas 14 IDF values shows a ±27% difference in over 95% of the state for all storm durations. The median of the difference stays between −10% and +10% for all storm durations and for all return periods in the range of (2–100) years. The mean difference ranges from −5% for the 100-year return period to 8% for the 10-year return period for the 24-h storm. Generally, the western and northern regions of the state show an overestimation, while the southern and southcentral regions show an underestimation of the published values

Brief Communication: Analysis of the Fatalities and Socio-Economic Impacts Caused by Hurricane Florence

Florence made landfall on the southeastern coast of North Carolina (NC) generating torrential rainfall and severe flooding that led to 53 fatalities in three states (NC, SC, and VA) and 16⁻40 billion in damage. Seventy-seven percent (77%) of the fatalities occurred in the rural flood plains of NC with Duplin county reporting a high of eight deaths. Approximately 50% of the total number of hurricane-related fatalities across the three states were vehicle-related. The predominant demographic at risk were males over the age of 50 years. The type of property damage was in line with other major hurricanes and predominantly affected residential structures (93% of the total number of damaged buildings). Florence is among the top 10 costliest hurricanes in U.S. history with approximately 50% of the damage projected as uninsured losses due to residential flooding. The cumulative 5-day rainfall resulted in major flooding along the Cape Fear, Lumberton, and Neuse rivers where many industrial waste sites (hog manure lagoons and coal ash pits) are located. Several of these waste sites located in the flood plain were breached and have likely cross-contaminated the waterways and water treatment operations. The observed extent of the flooding, environmental contamination, and impact to public health caused by Florence will add to the long-term disaster related mortality and morbidity rates and suggests an expansion of the 100-yr flood hazard zone to communicate the expanded risk to the public

Assessment of the Performance of Satellite-Based Precipitation Products for Flood Events across Diverse Spatial Scales Using GSSHA Modeling System

Accurate precipitation measurements for high magnitude rainfall events are of great importance in hydrometeorology and climatology research. The focus of the study is to assess the performance of satellite-based precipitation products against a gauge adjusted Next-Generation Radar (NEXRAD) Stage IV product during high magnitude rainfall events. The assessment was categorized across three spatial scales using watershed ranging from ~200–10,000 km2. The propagation of the errors from rainfall estimates to runoff estimates was analyzed by forcing a hydrologic-model with the satellite-based precipitation products for nine storm events from 2004 to 2015. The National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) Morphing Technique (CMORPH) products showed high correlation to the NEXRAD estimates in all spatial domains, and had an average Nash-Sutcliffe coefficient of 0.81. The Global Precipitation Measurement (GPM) Early product was inconsistent with a very high variance of Nash-Sutcliffe coefficient in all spatial domains (from −0.46 to 0.38), however, the variance decreased as the watershed size increased. Surprisingly, Tropical Rainfall Measuring Mission (TRMM) also showed a very high variance in all the performance statics. In contrast, the un-corrected product of the TRMM showed a relatively better performance. The errors of the precipitation estimates were amplified in the simulated hydrographs. Even though the products provide evenly distributed near-global spatiotemporal estimates, they significantly underestimate strong storm events in all spatial scales

A multi-satellite approach for water storage monitoring in an arid watershed

The objective of this study was to use satellite imagery to monitor the water budget of Al Ain region in the United Arab Emirates (UAE). Inflows and outflows were estimated and the trend of water storage variation in the study area was examined from 2005 to 2014. Evapotranspiration was estimated using the simplified Penman-Monteith equation. Landsat images were used to determine the extent of agricultural and green areas. Time series of gravity recovery and climate experiment (GRACE) observations over the study area were used to assess the inferred water storage variation from satellite data. The change of storage inferred from the Water Budget Equation showed a decreasing trend at an average rate of 2.57 Mm3 annually. Moreover, GRACE readings showed a decreasing trend at a rate of 0.35 cm of water depth annually. Mann-Kendal, a non-parametric trend test, proved the presence of significant negative trends in both time series at a 5% significance level. A two-month lag resulted in a better agreement (R2 = 0.55) between the change in water storage and GRACE anomalies within the study area. These results suggest that water storage in the study area is being depleted significantly. Moreover, the potential of remote sensing in water resource management, especially in remote and arid areas, was demonstrated

A multi-satellite approach for water storage monitoring in an arid watershed

The objective of this study was to use satellite imagery to monitor the water budget of Al Ain region in the United Arab Emirates (UAE). Inflows and outflows were estimated and the trend of water storage variation in the study area was examined from 2005 to 2014. Evapotranspiration was estimated using the simplified Penman-Monteith equation. Landsat images were used to determine the extent of agricultural and green areas. Time series of gravity recovery and climate experiment (GRACE) observations over the study area were used to assess the inferred water storage variation from satellite data. The change of storage inferred from the Water Budget Equation showed a decreasing trend at an average rate of 2.57 Mm3 annually. Moreover, GRACE readings showed a decreasing trend at a rate of 0.35 cm of water depth annually. Mann-Kendal, a non-parametric trend test, proved the presence of significant negative trends in both time series at a 5% significance level. A two-month lag resulted in a better agreement (R2 = 0.55) between the change in water storage and GRACE anomalies within the study area. These results suggest that water storage in the study area is being depleted significantly. Moreover, the potential of remote sensing in water resource management, especially in remote and arid areas, was demonstrated

A multi-satellite approach for water storage monitoring in an arid watershed

The objective of this study was to use satellite imagery to monitor the water budget of Al Ain region in the United Arab Emirates (UAE). Inflows and outflows were estimated and the trend of water storage variation in the study area was examined from 2005 to 2014. Evapotranspiration was estimated using the simplified Penman-Monteith equation. Landsat images were used to determine the extent of agricultural and green areas. Time series of gravity recovery and climate experiment (GRACE) observations over the study area were used to assess the inferred water storage variation from satellite data. The change of storage inferred from the Water Budget Equation showed a decreasing trend at an average rate of 2.57 Mm3 annually. Moreover, GRACE readings showed a decreasing trend at a rate of 0.35 cm of water depth annually. Mann-Kendal, a non-parametric trend test, proved the presence of significant negative trends in both time series at a 5% significance level. A two-month lag resulted in a better agreement (R2 = 0.55) between the change in water storage and GRACE anomalies within the study area. These results suggest that water storage in the study area is being depleted significantly. Moreover, the potential of remote sensing in water resource management, especially in remote and arid areas, was demonstrated

Assessment of the consistency among global precipitation products over the United Arab Emirates

Study region: United Arab Emirates. Study focus: Numerous global precipitation products have been developed and calibrated. However, their performance over arid regions such as the United Arab Emirates (UAE) has been revealing notable differences triggered by a combination of climatic and terrestrial attributes. The objective of this study is to cross-validate and analyze the consistency of four global precipitation products from the GPCC, TRMM, WM, and CMORPH datasets over the UAE using a network of 53 rain gauges from 2000 to 2010. The spatial analysis of their consistency versus topography and land cover is expected to reveal the factors affecting the country’s rainfall regime. The study also identifies and calibrates the best statistically performing precipitation product as an essential climatic input for monitoring, forecasting, and modeling hydrologic applications over the UAE. New hydrological insights for the region: The UAE, similar to other dryland environments lacking adequate hydrologic monitoring networks, presents a unique area to evaluate satellite remote sensing products and the erratic spatiotemporal nature of precipitation in diverse environments. Statistical analyses indicate that the TMPA V7 precipitation products record the highest overall agreement with the observational network. Within the UAE, areas that receive high rainfall and fall within the vegetated highlands (e.g., >250 m), provide the most promise for incorporating satellite precipitation into hydrologic monitoring, modeling, or water resource management