Kuo Hsin Tseng

Discharge and water‐depth estimates for ungauged rivers: Combining hydrologic, hydraulic, and inverse modeling with stage and water‐area measurements from satellites

Anticipating future global freshwater scarcity and providing mitigation require timely knowledge of spatiotemporal dynamics of discharge for gauged and, more challengingly, ungauged rivers. This study describes a coupled hydrologic (SWAT) and hydraulic (XSECT) modeling approach set in a genetic algorithm framework for estimating discharge and water depth for ungauged rivers from space. The method was tested in the Red River of the North basin by comparing simulated discharges and depths from 2006 to 2010 to in situ observations from across the basin. Results showed that calibration using only remotely sensed data (i.e., water levels from ENVISAT altimetry and water extents from LANDSAT) along the main stem of the Red River yielded daily and monthly estimates of river discharge, which correlated to measured discharges at three gaging stations on the main stem with R2 values averaging 0.822 and 0.924, respectively. The comparisons of modeled and measured discharges were also extended to smaller tributaries, yielding a mean R2 of 0.809 over seven gaging stations. The modeling approach also provided estimates of water depth that correlated to observations at four stations with an average R2 of 0.831. We conclude that the integrated modeling approach is able to estimate discharge and water depth from space for larger ungauged rivers. This study also implies that in situ discharge data may not be necessary for successful hydrologic model calibration.

Integrating Landsat Imageries and Digital Elevation Models to Infer Water Level Change in Hoover Dam

The Thematic Mapper onboard Landsat 4, 5, and Enhanced Thematic Mapper Plus (TM/ETM+) onboard Landsat 7 have frequency bands (green and SWIR) to effectively measure water body extents and their changes via the Modified Normalized Difference Water Index (MNDWI). Here, we developed a technique, called the thematic imagery-altimetry system (TIAS), to infer the vertical water changes from MNDWI horizontal water extent changes by integrating long-term TM/ETM+ imageries with available digital elevation models (DEMs). The result is a technique to quantify water level changes of natural or artificial water bodies over two decades. Several DEMs were used to compute intersects with TM/ETM+ water extent time series to evaluate the robustness of the technique. These DEMs include: the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Map version 2 (ASTER-GDEM2, at 1 arcsec resolution), the Shuttle Radar Topography Mission version 2 (SRTM C-band at 1 arcsec), and the Global Multiresolution Terrain Elevation Data (GMTED2010 at 7.5 arcsec). We demonstrated our technique near Hoover Dam (HD) in Lake Mead to quantify its respective decadal water level.

Assessment of the Impact of Reservoirs in the Upper Mekong River Using Satellite Radar Altimetry and Remote Sensing Imageries

Water level (WL) and water volume (WV) of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite radar altimetry (RA, Envisat and Jason-2) and Landsat-5/-7/-8 Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+)/Operational Land Imager (OLI) optical remote sensing (RS) imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between WL variation and water extent was first established for each dam, and then the combined long-term WL time series from Landsat images are reconstructed for the dams. The R2 between altimetry WL and Landsat water area measurements is >0.95. Next, the Tropical Rainfall Measuring Mission (TRMM) data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in situ gauge data, in term of root-mean-square error (RMSE) is at 2–5 m level. The estimated WV variations derived from combined RA/RS imageries and digital elevation model (DEM) are consistent with results from in situ data with a difference at about 3%. We concluded that the river level downstream is affected by a combined operation of these two dams after 2009, which has decreased WL by 0.20 m·year−1 in wet seasons and increased WL by 0.35 m·year−1 in dry seasons.

Terrestrial Water Storage in African Hydrological Regimes Derived from GRACE Mission Data: Intercomparison of Spherical Harmonics, Mass Concentration, and Scalar Slepian Methods

Spherical harmonics (SH) and mascon solutions are the two most common types of solutions for Gravity Recovery and Climate Experiment (GRACE) mass flux observations. However, SH signals are degraded by measurement and leakage errors. Mascon solutions (the Jet Propulsion Laboratory (JPL) release, herein) exhibit weakened signals at submascon resolutions. Both solutions require a scale factor examined by the CLM4.0 model to obtain the actual water storage signal. The Slepian localization method can avoid the SH leakage errors when applied to the basin scale. In this study, we estimate SH errors and scale factors for African hydrological regimes. Then, terrestrial water storage (TWS) in Africa is determined based on Slepian localization and compared with JPL-mascon and SH solutions. The three TWS estimates show good agreement for the TWS of large-sized and humid regimes but present discrepancies for the TWS of medium and small-sized regimes. Slepian localization is an effective method for deriving the TWS of arid zones. The TWS behavior in African regimes and its spatiotemporal variations are then examined. The negative TWS trends in the lower Nile and Sahara at −1.08 and −6.92 Gt/year, respectively, are higher than those previously reported.

Quantifying Freshwater Mass Balance in the Central Tibetan Plateau by Integrating Satellite Remote Sensing, Altimetry, and Gravimetry

The Tibetan Plateau (TP) has been observed by satellite optical remote sensing, altimetry, and gravimetry for a variety of geophysical parameters, including water storage change. However, each of these sensors has its respective limitation in the parameters observed, accuracy and spatial-temporal resolution. Here, we utilized an integrated approach to combine remote sensing imagery, digital elevation model, and satellite radar and laser altimetry data, to quantify freshwater storage change in a twin lake system named Chibuzhang Co and Dorsoidong Co in the central TP, and compared that with independent observations including mass changes from the Gravity Recovery and Climate Experiment (GRACE) data. Our results show that this twin lake, located within the Tanggula glacier system, remained almost steady during 1973–2000. However, Dorsoidong Co has experienced a significant lake level rise since 2000, especially during 2000–2005, that resulted in the plausible connection between the two lakes. The contemporary increasing lake level signal at a rate of 0.89 ± 0.05 cm·yr−1, in a 2° by 2° grid equivalent water height since 2002, is higher than the GRACE observed trend at 0.41 ± 0.17 cm·yr−1 during the same time span. Finally, a down-turning trend or inter-annual variability shown in the GRACE signal is observed after 2012, while the lake level is still rising at a consistent rate.