DEVELOPMENT AND EVALUATION OF AN ADVANCED REGIONAL AND GLOBAL HYDROLOGICAL PREDICTION SYSTEM ENABLED BY SATELLITE REMOTE SENSING, NUMERICAL WEATHER FORECASTING, AND ENSEMBLE DATA ASSIMILATION

This dissertation advanced the traditional hydrological prediction via multi-sensor satellite remote sensing products, numerical weather forecasts and advanced data assimilation approach in sparsely gauged or even ungauged regions and then extend this approach to global scale with enhanced efficiency for prototyping a flood early warning system on a global basis. This dissertation consists of six chapters: the first chapter is the introductive chapter which describes the problem and raises the hypotheses, Chapters 2 to 5 are the four main Chapters followed by Chapter 6 which is an overall summary of this dissertation. For regional hydrological prediction in Chapter 2 and 3, two rainfall – runoff hydrological models: the HyMOD (Hydrological MODel) and the simplified version of CREST (Coupled Routing and Excess Storage) Model were set up and tested in Cubango River basin, Africa. In Chapter 2, first, the AMSR-E (Advanced Microwave Scanning Radiometer for Earth observing system) signal/TMI (TRMM Microwave Imager) passive microwave streamflow signals are converted into actual streamflow domain with the unit of m3/s by adopting the algorithm from Brakenridge et al. (2007); then the HyMOD was coupled with Ensemble Square Root Filter (EnSRF) to account for uncertainty in both forcing data and model initial conditions and thus improve the flood prediction accuracy by assimilating the signal converted streamflow, in comparison to the benchmark assimilation of in-situ streamflow observations in actual streamflow domain with the unit of m3/s. In Chapter 3, the remote-sensing streamflow signals, without conventional in-situ hydrological measurements, was applied to force, calibrate and update the hydrologic model coupled with EnSRF data assimilation approach in the same research region, but resulting in exceedance probability-based flood prediction. For global hydrological predictions in Chapter 4 and 5, a physical based distributed hydrological model CREST is set up at 1/8 degree from 50°N to 50°S and forms the Real Time Hydrological Prediction System (http://eos.ou.edu) which was co-developed by HyDROS (Hydrometeorology and Remote Sensing Laboratory) lab at the University of Oklahoma and NASA Goddard center. In Chapter 4, the CREST model is described with details and then the Real Time Global Hydrological Monitoring System will be comprehensively evaluated on basis of gauge based streamflow observation and gridded global runoff data from GRDC (Global Runoff Data Center, http://www.bafg.de/GRDC/EN/Home/homepage_node.html). In order to extend the hydrological forecast horizon for the Real Time Global Hydrological Prediction System, the deterministic precipitation forecast fields from a numerical meteorological model GFS (Global Forecasting System) as well as the ensemble precipitation forecast fields are introduced as the forcing data to be coupled into the global CREST model in order to generate the global hydrological forecasting up to around 7 days lead time in Chapter 5. The July 21, 2012 Beijing extreme flooding event is selected to evaluate the hydrological prediction skills for extremes of both the deterministic and the ensemble GFS products

Decadal development of CREST hydrological model family: review, improvements, applications, and outlook

A hydrological model is an indispensable tool in Earth system science and engineering operations to understand, predict, and manage water resources on Earth. The Coupled Routing and Excess Storage (CREST) model, released in 2011, is one such to simulate distributed hydrologic states and fluxes at variable scales. Over the last decade, CREST model has been actively under development and applied by different sectors to tackle water-related problems worldwide. This dissertation is dedicated to expanding the capacity of CREST model from three main fronts: (1) hydrologic data, (2) model development, and (3) applications. To start, the decadal development and applications of CREST model family were reviewed to lay the foundation for my contribution (Chapter 1). First, uncertainties in hydrologic input data were evaluated comprehensively for three state-of-the-science precipitation datasets derived from in-situ instruments, ground weather radar, and satellites during extreme events (Chapter 2); then a 120-year CONUS-wide flood database was compiled into a unified format as a validation source for models and hydroclimatic research (Chapter 3). From the model development front, a Hydrologic&Hydraulic (H&H) framework was developed to empower flood inundation mapping capacity for CREST (Chapter 4); furthermore, the re-infiltration, an important yet often ignored hydrologic process during the flooding period, was incorporated to improve the more realistic rainfall-runoff modeling representation (Chapter 5). To further improve the model efficiency, a vector-based CREST model was developed that can achieve 10x speedup for a continental-scale simulation, as well as improved model accuracy (Chapter 6). Finally on the model application, the high-resolution CREST model was applied in quantifying future US floods in a warmer climate: flood flashiness is becoming 7.9% higher for the continent (Chapter 7); and extreme rainfall and floods are becoming more frequent, widespread, and less seasonal (Chapter 8). The final Chapter 9 summarizes the contributions to the CREST model family development, outlooks, and general remarks for advancing our understanding of hydrologic science and engineering

An overview of monitoring methods for assessing the performance of nature-based solutions against natural hazards

To bring to fruition the capability of nature-based solutions (NBS) in mitigating hydro-meteorological risks (HMRs) and facilitate their widespread uptake require a consolidated knowledge-base related to their monitoring methods, efficiency, functioning and the ecosystem services they provide. We attempt to fill this knowledge gap by reviewing and compiling the existing scientific literature on methods, including ground-based measurements (e.g. gauging stations, wireless sensor network) and remote sensing observations (e.g. from topographic LiDAR, multispectral and radar sensors) that have been used and/or can be relevant to monitor the performance of NBS against five HMRs: floods, droughts, heatwaves, landslides, and storm surges and coastal erosion. These can allow the mapping of the risks and impacts of the specific hydro-meteorological events. We found that the selection and application of monitoring methods mostly rely on the particular NBS being monitored, resource availability (e.g. time, budget, space) and type of HMRs. No standalone method currently exists that can allow monitoring the performance of NBS in its broadest view. However, equipments, tools and technologies developed for other purposes, such as for ground-based measurements and atmospheric observations, can be applied to accurately monitor the performance of NBS to mitigate HMRs. We also focused on the capabilities of passive and active remote sensing, pointing out their associated opportunities and difficulties for NBS monitoring application. We conclude that the advancement in airborne and satellite-based remote sensing technology has signified a leap in the systematic monitoring of NBS performance, as well as provided a robust way for the spatial and temporal comparison of NBS intervention versus its absence. This improved performance measurement can support the evaluation of existing uncertainty and scepticism in selecting NBS over the artificially built concrete structures or grey approaches by addressing the questions of performance precariousness. Remote sensing technical developments, however, take time to shift toward a state of operational readiness for monitoring the progress of NBS in place (e.g. green NBS growth rate, their changes and effectiveness through time). More research is required to develop a holistic approach, which could routinely and continually monitor the performance of NBS over a large scale of intervention. This performance evaluation could increase the ecological and socio-economic benefits of NBS, and also create high levels of their acceptance and confidence by overcoming potential scepticism of NBS implementations

Moraine-dammed glacial lakes and threat of glacial debris flows in South-East Kazakhstan

Glacier retreat has caused the emergence of numerous moraine-dammed glacial lakes (MGL) over the last century which have become research foci in many mountain regions of the world. Outbursts of MGLs have caused destructive floods and debris flows, leading to numerous human casualties and significant material damage. The mountains of South-Eastern Kazakhstan have also become prone to lake outburst floods and related debris flows, specifically in the second half of the 20th century. This paper presents and reviews existing surveys and knowledge along with results of own investigations on the formation of MGLs and the characteristics of lake outburst floods and debris flows in the Kazakh part of Tien Shan. We suggest a workflow to identify the most dangerous types of lakes and provide information about their morphogenetic features and hazard criteria. The number of MGLs increased since the 1970s with more than 160 existing in 2018. Forty were identified as being dangerous. Forty-eight lake outbursts occurred since 1950 with all the documented events happened between end of June and end of August. The most dangerous outbursts were caused by ruptures in ice-cored moraine dams. Outbursts of nine MGLs caused disastrous debris flows, with some occurring repeatedly. The number of outbursts clearly decreased since the year 2000 compared to 1970–2000. However, due to ongoing glacier retreat new lakes are forming at higher altitudes. Their greater potential energy makes possible future outbursts more dangerous. Re-evaluation of existing methods to calculate the water volume and peak discharge based on bathymetric measurements and observed outbursts revealed that the applied equations provide suitable approximations and allow supporting mitigation and prevention measures. Finally, the presentation of implemented measures to lower the water level using siphons or artificial flow channels shows that they can reduce the lake outburst hazards. However, they are associated with risks and financial costs and it needs to be carefully considered whether protection measures of the endangered areas are more cost effective.Publisher PDFPeer reviewe

Stream network analysis and geomorphic flood plain mapping from orbital and suborbital remote sensing imagery application to flood hazard studies in central Texas

The author has identified the following significant results. Development of a quantitative hydrogeomorphic approach to flood hazard evaluation was hindered by (1) problems of resolution and definition of the morphometric parameters which have hydrologic significance, and (2) mechanical difficulties in creating the necessary volume of data for meaningful analysis. Measures of network resolution such as drainage density and basin Shreve magnitude indicated that large scale topographic maps offered greater resolution than small scale suborbital imagery and orbital imagery. The disparity in network resolution capabilities between orbital and suborbital imagery formats depends on factors such as rock type, vegetation, and land use. The problem of morphometric data analysis was approached by developing a computer-assisted method for network analysis. The system allows rapid identification of network properties which can then be related to measures of flood response

Sand mining in the Mekong Delta revisited - current scales of local sediment deficits

The delta of the Mekong River in Vietnam has been heavily impacted by anthropogenic stresses in recent years, such as upstream dam construction and sand mining within the main and distributary channels, leading to riverbank and coastal erosion. Intensive bathymetric surveys, conducted within the Tien River branch during the dry and wet season 2018, reveal a high magnitude of sand mining activities. For the year 2018, an analysis of bathymetric maps and the local refilling processes leads to an estimated sand extraction volume of 4.64 ± 0.31 Mm3/yr in the study area, which covered around 20 km. Reported statistics of sand mining for all of the Mekong’s channels within the delta, which have a cumulative length of several hundred kilometres, are 17.77 Mm3/yr for this period. Results from this study highlight that these statistics are likely too conservative. It is also shown that natural sediment supplies from upper reaches of the Mekong are insufficient to compensate for the loss of extracted bed aggregates, illustrating the non-sustainable nature of the local sand mining practices