To promote the advancement of novel observation techniques that may lead to new sources of information to help better understand the hydrological cycle, the International Association of Hydrological Sciences (IAHS) established the Measurements and Observations in the XXI century (MOXXI) Working Group in July 2013 The group comprises a growing community of tech-enthusiastic hydrologists that design and develop their own sensing systems, adopt a multi-disciplinary perspective in tackling complex observations, often use low-cost equipment intended for other applications to build innovative sensors, or perform opportunistic measurements This paper states the objectives of the group and reviews major advances carried out by MOXXI members toward the advancement of hydrological sciences Challenges and opportunities are outlined to provide strategic guidance for advancement of measurement, and thus discovery

/pdf/measurements-and-observations-in-the-xxi-century-moxxi-58wga5k3uk.pdf

Measurements and Observations in the XXI century (MOXXI): innovation and multi-disciplinarity to sense the hydrological cycle

Discharge estimation in high-mountain regions with improved methods using multisource remote sensing: A case study of the Upper Brahmaputra River

River discharge estimation at daily resolution from satellite altimetry over an entire river basin

An improved approach to monitoring Brahmaputra River water levels using retracked altimetry data

Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River

Limitations of satellite radar altimetry for operational hydrology include its spatial and temporal sampling as well as measurement problems caused by local topography and heterogeneity of the reflecting surface. In this study, we develop an approach that eliminates most of these limitations to produce an approximately 3 day temporal resolution water level time series from the original typically (sub)monthly data sets for the Po River in detail, and for Congo, Mississippi, and Danube Rivers. We follow a geodetic approach by which, after estimating and removing intersatellite biases, all virtual stations of several satellite altimeters are connected hydraulically and statistically to produce water level time series at any location along the river. We test different data-selection strategies and validate our method against the extensive available in situ data over the Po River, resulting in an average correlation of 0.7, Root-Mean-Square Error of 0.8 m, bias of −0.4 m, and Nash-Sutcliffe Efficiency coefficient of 0.5. We validate the transferability of our method by applying it to the Congo, Mississippi, and Danube Rivers, which have very different geomorphological and climatic conditions. The methodology yields correlations above 0.75 and Nash-Sutcliffe coefficients of 0.84 (Congo), 0.34 (Mississippi), and 0.35 (Danube).

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015WR017654

T. Qin

Papers

Spatiotemporal densification of river water level time series by multimission satellite altimetry