Flow duration curves from surface reflectance in the near infrared band

Flow duration curve (FDC) is a cumulative frequency curve that shows the percent of time a specific discharge has been equaled or exceeded during a particular period of time at a given river location, providing a comprehensive description of the hydrological regime of a catchment. Thus, relying on historical streamflow records, FDCs are typically constrained to gauged and updated ground stations. Earth Observations can support our monitoring capability and be considered as a valuable and additional source for the observation of the Earth’s physical parameters. Here, we investigated the potential of the surface reflectance in the Near Infrared (NIR) band of the MODIS 500 m and eight-day product, in providing reliable FDCs along the Mississippi River. Results highlight the capability of NIR bands to estimate the FDCs, enabling a realistic reconstruction of the flow regimes at different locations. Apart from a few exceptions, the relative Root Mean Square Error, rRMSE, of the discharge value in validation period ranges from 27–58% with higher error experienced for extremely high flows (low duration), mainly due to the limit of the sensor to penetrate the clouds during the flood events. Due to the spatial resolution of the satellite product higher errors are found at the stations where the river is narrow. In general, good performances are obtained for medium flows, encouraging the use of the satellite for the water resources management at ungauged river sites

Toward the estimation of river discharge variations using MODIS data in ungauged basins

This study investigates the capability of the Moderate resolution Imaging Spectroradiometer (MODIS) to estimate river discharge, even for ungauged sites. Because of its frequent revisits (as little as every 3 h) and adequate spatial resolution (250 m), MODIS bands 1 and 2 have significant potential for mapping the extent of flooded areas and estimating river discharge even for medium-sized basins. Specifically, the different behaviour of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum is exploited by computing the ratio (C/M) of the MODIS channel 2 reflectance values between two pixels located within (M) and outside (C), but close to, the river. The values of C/M increase with the presence of water and, hence, with discharge. Moreover, in order to reduce the noise effects due to atmospheric contribution, an exponential smoothing filter is applied, thus obtaining C/M⁎. Time series of hourly mean flow velocity and discharge between 2005 and 2011 measured at four gauging stations located along the Po river (Northern Italy) are employed for testing the capability of C/M⁎ to estimate discharge/flow velocity. Specifically, the meanders and urban areas are considered the best locations for the position of the pixels M and C, respectively. Considering the optimal pixels, the agreement between C/M⁎ and discharge/flow velocity is fairly good with values in the range of 0.65–0.77. Additionally, the application to ungauged sites is tested by deriving a unique regional relationship between C/M⁎ and flow velocity valid for the whole Po river and providing only a slight deterioration of the performance. Finally, the sensitivity of the results to the selection of the C and M pixels is investigated by randomly changing their location. Also in this case, the agreement with in situ observations of velocity is fairly satisfactory (r ~ 0.6). The obtained results demonstrate the capability of MODIS to monitor discharge (and flow velocity). Therefore, its application for a larger number of sites worldwide will be the object of future studies

Utilizzo di un modello diffusivo 2D di acque basse PER LA simulazione in tempo reale di scenari di inondazioni

I recenti cambiamenti climatici e le sempre più frequenti inondazioni rendono particolarmente attuale l’utilizzo di sistemi di allerta per facilitare l’evacuazione precoce della popolazione e la messa in sicurezza dei beni. I suddetti sistemi sono basati in parte sulla previsione a breve termine delle piogge, in parte sulla stima del processo di trasformazione afflussi-deflussi e della propagazione dell’onda di piena. Nella presente memoria il modello diffusivo MAST 2D ad avanzamento spaziale e temporale già proposto da alcuni degli autori viene ulteriormente migliorato per una più rapida soluzione ed una migliore adattabilità all’uso del calcolo parallelo. Viene introdotta una nuova soluzione semi-analitica della componente convettiva del problema, con una notevole riduzione del corrispondente sforzo computazionale. La componente diffusiva viene discretizzata nello spazio e nel tempo con una procedura classica agli elementi finiti che si traduce, ad ogni passo temporale, in un sistema lineare ben condizionato che può essere risolto efficacemente anche con l’ausilio del calcolo parallelo. Il modello è stato implementato nel sistema di allerta precoce del fiume Genna, in Umbria. Gli idrogrammi di piena previsti a breve termine sulla base delle pioggie misurate sono utilizzati quali condizione al contorno di monte del modello, il cui dominio ricopre la superficie potenzialmente inondabile per tutto il tratto considerato a rischio idraulico. Il tempo di calcolo necessario a simulare accuratamente la propagazione della piena è un decimo della durata dell’idrogramma di piena e ancor più piccolo rispetto all’anticipo delle previsioni di pioggia rispetto al verificarsi dell’inondazione

Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data

Effective agricultural water management requires accurate and timely information on the availability and use of irrigation water. However, most existing information on irrigation water use (IWU) lacks the objectivity and spatiotemporal representativeness needed for operational water management and meaningful characterization of land–climate interactions. Although optical remote sensing has been used to map the area affected by irrigation, it does not physically allow for the estimation of the actual amount of irrigation water applied. On the other hand, microwave observations of the moisture content in the top soil layer are directly influenced by agricultural irrigation practices and thus potentially allow for the quantitative estimation of IWU. In this study, we combine surface soil moisture (SM) retrievals from the spaceborne SMAP, AMSR2 and ASCAT microwave sensors with modeled soil moisture from MERRA-2 reanalysis to derive monthly IWU dynamics over the contiguous United States (CONUS) for the period 2013–2016. The methodology is driven by the assumption that the hydrology formulation of the MERRA-2 model does not account for irrigation, while the remotely sensed soil moisture retrievals do contain an irrigation signal. For many CONUS irrigation hot spots, the estimated spatial irrigation patterns show good agreement with a reference data set on irrigated areas. Moreover, in intensively irrigated areas, the temporal dynamics of observed IWU is meaningful with respect to ancillary data on local irrigation practices. State-aggregated mean IWU volumes derived from the combination of SMAP and MERRA-2 soil moisture show a good correlation with statistically reported state-level irrigation water withdrawals (IWW) but systematically underestimate them. We argue that this discrepancy can be mainly attributed to the coarse spatial resolution of the employed satellite soil moisture retrievals, which fails to resolve local irrigation practices. Consequently, higher-resolution soil moisture data are needed to further enhance the accuracy of IWU mapping.</p

High-resolution satellite products improve hydrological modeling in northern Italy

Satellite-based Earth observations (EO) are an accurate and reliable data source for atmospheric and environmental science. Their increasing spatial and temporal resolutions, as well as the seamless availability over ungauged regions, make them appealing for hydrological modeling. This work shows recent advances in the use of high-resolution satellite-based EO data in hydrological modeling. In a set of six experiments, the distributed hydrological model Continuum is set up for the Po River basin (Italy) and forced, in turn, by satellite precipitation and evaporation, while satellite-derived soil moisture (SM) and snow depths are ingested into the model structure through a data-assimilation scheme. Further, satellite-based estimates of precipitation, evaporation, and river discharge are used for hydrological model calibration, and results are compared with those based on ground observations. Despite the high density of conventional ground measurements and the strong human influence in the focus region, all satellite products show strong potential for operational hydrological applications, with skillful estimates of river discharge throughout the model domain. Satellite-based evaporation and snow depths marginally improve (by 2 % and 4 %) the mean Kling–Gupta efficiency (KGE) at 27 river gauges, compared to a baseline simulation (KGEmean= 0.51) forced by high-quality conventional data. Precipitation has the largest impact on the model output, though the satellite data on average shows poorer skills compared to conventional data. Interestingly, a model calibration heavily relying on satellite data, as opposed to conventional data, provides a skillful reconstruction of river discharges, paving the way to fully satellite-driven hydrological applications.</p

Altimetry for the future: Building on 25 years of progress

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion

Altimetry for the future: building on 25 years of progress

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion

Preface: Remote sensing for flood mapping and monitoring of flood dynamics

This Special Issue is a collection of papers that focus on the use of remote sensing data and describe methods for flood monitoring and mapping. These articles span a wide range of topics; present novel processing techniques and review methods; and discuss limitations and challenges. This preface provides a brief overview of the content

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

Flooding is one of the most devastating natural hazards in the world and its forecast is essential in flood risk reduction and disaster response decision. The lack of adequate monitoring networks, especially in developing countries prevents near real-time flood prediction that could help to reduce the loss of lives and economic damages. In the last few years, increasing availability of multi-satellite sensors induced to develop new techniques for retrieving river discharge and especially in supporting discharge nowcasting and forecasting activities. Recently, the potential of radar altimetry to estimate water levels and discharge in ungauged river sites with good accuracy has been demonstrated. However, the considerable benefit derived from this technique is attenuated by the low revisit time of the satellite (10 or 35 days, depending on the satellite mission) causing delays on the predicting operations. For this reason, sensors with a higher temporal resolution such as the MODerate resolution Imaging Spectroradiometer (MODIS), working in visible/Infra-Red bands, can support flood forecasting. In this study, we performed the forecast of river discharge by using MODIS and we compared it with the radar altimetry and in-situ data along the Niger-Benue River in Nigeria to develop an operational flood forecasting scheme that could help in rapid emergency response and decision making processes. In the first step, four MODIS products (daily and, 8-day from the TERRA and AQUA satellites) at two gauged sites were used for discharge estimation. Secondly, the capability of remote sensing sensors to forecast discharge a few days (~4 days) in advance at a downstream section using MODIS is analyzed and also compared with the one obtained by the use of radar altimetry by ENVISAT and Jason-2. The results confirmed the capability of the MODIS data to estimate river discharge with performance indices N0.97 and 0.95 in terms of coefficient of correlation and Nash Sutcliffe efficiency. In particular, RMSE does not exceed 1300 m3 /s and the fractional RMSE ranges between 0.15 and 0.23. For the forecasting exercise, both altimetry and MODIS provide satisfactory results with positive coefficient of persistence considering 4 days of lead time (N0.34). Although altimetry was found to be more accurate in the forecasting of river discharge (RMSE ~350 m3 /s), the much higher temporal resolution of MODIS guarantees a continuity that is more suitable to address operational activities