Earth Observation (EO) data is a critical information source for mapping and monitoring water resources over large inaccessible regions where hydrological in-situ networks are sparse. In this paper, ...we present a simple yet robust method for fusing optical and Synthetic Aperture Radar (SAR) data for mapping surface water dynamics over mainland China. This method uses a multivariate logistic regression model to estimate monthly surface water extent over a four-year period (2017 to 2020) from the combined usages of Sentinel-1, Sentinel-2 and Landsat-8 imagery. Multi-seasonal high-resolution images from the Chinese Gaofen satellites are used as a reference for an independent validation showing a high degree of agreement (overall accuracy 94%) across a diversity of climatic and physiographic regions demonstrating potential scalability beyond China. Through inter-comparison with similar global scale products, this paper further shows how this new mapping technique provides improved spatio-temporal characterization of inland water bodies, and for better capturing smaller water bodies (< 0.81 ha in size). The relevance of the results is discussed, and we find this new enhanced monitoring approach has the potential to advance the use of Earth observation for water resource management, planning and reporting.
Climate change, increasing population and changes in land use are all rapidly driving the need to be able to better understand surface water dynamics. The targets set by the United Nations under ...Sustainable Development Goal 6 in relation to freshwater ecosystems also make accurate surface water monitoring increasingly vital. However, the last decades have seen a steady decline in in situ hydrological monitoring and the availability of the growing volume of environmental data from free and open satellite systems is increasingly being recognized as an essential tool for largescale monitoring of water resources. The scientific literature holds many promising studies on satellite-based surface-water mapping, but a systematic evaluation has been lacking. Therefore, a round robin exercise was organized to conduct an intercomparison of 14 different satellite-based approaches for monitoring inland surface dynamics with Sentinel-1, Sentinel-2, and Landsat 8 imagery. The objective was to achieve a better understanding of the pros and cons of different sensors and models for surface water detection and monitoring. Results indicate that, while using a single sensor approach (applying either optical or radar satellite data) can provide comprehensive results for very specific localities, a dual sensor approach (combining data from both optical and radar satellites) is the most effective way to undertake largescale national and regional surface water mapping across bioclimatic gradients.
Mapping and prediction of inundated areas are increasingly important for climate change adaptation and emergency preparedness. Flood forecasting tools and flood risk models have to be compared to ...observe flooding patterns for training, calibration, validation, and benchmarking. At the regional to continental scales, satellite earth observation (EO) is the established method for surface water extent (SWE) mapping, and several operational global-scale data products are available. However, the spatial resolution of satellite-derived SWE maps remains a limiting factor, especially in low-lying areas with complex hydrography, such as Denmark. We collected thermal imagery using an unmanned airborne system (UAS) for three areas in Denmark shortly after major flooding events. We combined the thermal imagery with an airborne lidar-derived high-resolution digital surface model of the country to retrieve high-resolution (40 cm) SWE maps. The resulting SWE maps were compared with low-resolution SWE maps derived from satellite earth observation and with potential flooded areas derived from the high-resolution digital elevation model. We conclude that UASs have significant potential for SWE mapping at intermediate scales (up to a few square kilometers), can bridge the scale gap between ground observations and satellite EO, and can be used to benchmark and validate SWE mapping products derived from satellite EO as well as models predicting inundation.
The paper presents results on the use of NOAA AVHRR data for desertification monitoring on a regional–global level. It is based on processing of the GIMMS 8 km global NDVI data set. Time series of ...annually integrated and standardized annual NDVI anomalies were generated and compared with a corresponding rainfall data set (1981–2003).
The regions studied include the Mediterranean basin, the Sahel from the Atlantic to the Red Sea, major parts of the drylands of Southern Africa, China–Mongolia and the drylands of South America, i.e. important parts of the desertification prone drylands of the world.
It is concluded that the suggested methodology is a robust and reliable way to assess and monitor vegetation trends and related desertification on a regional–global scale. A strong general relationship between NDVI and rainfall over time is demonstrated for considerable parts of the drylands. The results of performed trend analysis cannot be used to verify any systematic generic land degradation/desertification trend at the regional–global level. On the contrary, a “greening-up” seems to be evident over large regions.
The Water Observation and Information System (WOIS) is an open source software tool for monitoring, assessing and inventorying water resources in a cost-effective manner using Earth Observation (EO) ...data. The WOIS has been developed by, among others, the authors of this paper under the TIGER-NET project, which is a major component of the TIGER initiative of the European Space Agency (ESA) and whose main goal is to support the African Earth Observation Capacity for Water Resource Monitoring. TIGER-NET aims to support the satellite-based assessment and monitoring of water resources from watershed to cross-border basin levels through the provision of a free and powerful software package, with associated capacity building, to African authorities. More than 28 EO data processing solutions for water resource management tasks have been developed, in correspondence with the requirements of the participating key African water authorities, and demonstrated with dedicated case studies utilizing the software in operational scenarios. They cover a wide range of themes and information products, including basin-wide characterization of land and water resources, lake water quality monitoring, hydrological modeling and flood forecasting and mapping. For each monitoring task, step-by-step workflows were developed, which can either be adjusted by the user or largely automatized to feed into existing data streams and reporting schemes. The WOIS enables African water authorities to fully exploit the increasing EO capacity offered by current and upcoming generations of satellites, including the Sentinel missions.
•Multiple satellite missions are used to monitor water storage components in the NCP.•Sentinel-3 altimetry and spectral/SAR imagery are used to monitor surface water storage.•South-to-North Water ...Diversion project has a significant impact on regional water storage dynamics.
Natural conditions of surface water bodies and groundwater aquifers in the North China Plain (NCP) have been altered to meet the ever-growing human water demands. Several water resources management measures have been implemented in recent decades to alleviate groundwater depletion, maintain ecological resilience, and sustain agricultural production. This study aims to investigate their impacts on land water storage, and thus obtain a picture of the spatio-temporal variation of water resources over the NCP. Based on multi-mission earth observation datasets, i.e., altimetry (Sentinel-3), synthetic aperture radar (SAR) and spectral imagery (Sentinel-1/2), gravimetry (GRACE/-FO), and microwave sensors (IMERG), as well as reanalysis datasets, we investigate surface water storage (SWS), soil moisture water storage (SMS), and total water storage (TWS) changes. Groundwater storage (GWS) change is subsequently estimated as the residual of the total storage equation.
Results show that TWS declined significantly over the past decades (−1.04 ± 0.05 cm/yr in 2004 to 2020), while SMS rebounded after a decreasing trend from 2004 to 2014. The spatial pattern of TWS variations depicts a particularly severe depletion along provincial boundaries. The SWS dynamics reveal that the volumes of three major NCP reservoirs (Guanting, Miyun, and Danjiangkou) increased significantly since around 2014 when the operation of the South-to-North Water Diversion Middle Route project (SNWDP-MR) started. Moreover, GWS maintained a depletion rate of −1.05 ± 0.08 cm/yr during 2004–2014 over the whole NCP, while the depletion rate accelerated during 2015–2020 (−1.88 ± 0.38 cm/yr). We also found that the GWS depletion in Beijing (−1.20 ± 0.10 cm/yr during 2004–2014 and −0.79 ± 0.44 cm/yr during 2015–2020) and its surrounding areas has been lowered possibly because of the SNWDP-MR. This study shows how multi-mission satellite earth observation products can be combined to monitor water resources at a regional scale and provide spatio-temporally resolved estimates of the impacts of human-induced changes in the inland water cycle.
•We present a parameter transfer framework for poorly gauged river catchments.•We apply the approach in three African river catchments.•We evaluate spatial patterns of hydrological processes to ...assess model coherence.•Parameter transfer based on similarity outperforms transfer based on proximity.
Development of robust hydrologic-hydrodynamic simulation models is challenging, especially in regions, where in-situ observation data are scarce. Parameter calibration is often a necessary and data-demanding step. Moreover, good calibration performance does not guarantee predictive skill in neighboring geographic regions or new time periods and scenarios. A robust calibration strategy is necessary and must apply an informed parameter regionalization approach, which can transfer parameter values from gauged to ungauged subcatchments, whilst accounting for data availability and quality. In this study, a calibration strategy combining a parameter transfer framework based on catchment similarities with a holistic calibration against hydrological signatures is presented to obtain reliable simulations at all relevant locations within a catchment. The approach is demonstrated for three African river catchments: the Tana, the Upper Niger and the Semliki catchments.
A rainfall-runoff model based on Budyko’s concept of limits with up to 11 calibration parameters and a daily simulation time step is used, coupled with a Muskingum routing scheme. Each river catchment is subdivided into so-called hydrological response units (HRU) based on climatic and physiographic characteristics. Multi-mission satellite remote sensing observations are used for the HRU classification: terrain slope derived from the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) and the publicly available European Space Agency (ESA) Climate Change Initiative (CCI) land cover map. Subcatchments within each HRU share the same parameters. The number of units is constrained by the number of in-situ stations available. The calibration strategy is a catchment-scale, multi-objective approach.
The method improved the overall model performance compared to a simpler, nearest-neighbor regionalization method. In particular, spatial patterns of the hydrological response are more reasonable and performance is improved at validation stations, highlighting the importance of appropriate parameter regionalization within nested catchments. With this method, a wider range of currently available remote sensing data (elevation, precipitation, land cover, etc.) can be exploited in hydrological model development and calibration.
Reservoir release is an essential variable as it affects hydrological processes and water availability downstream. This study aims to estimate reservoir release using a satellite-based approach, ...specially focusing on the impacts of inflow simulations and reservoir water storage change (RWSC) on release estimates. Ten inflow simulations based on hydrological models and blending schemes are used in combination with three RWSC estimates based on two satellite-based approaches. A case study is performed at the Ankang reservoir, China. The results demonstrate that release estimates show high skill, with normalized root-mean-square error (NRMSE) less than 0.12 and Kling-Gupta Efficiency (KGE) over 0.65. The performance of release estimates is varying with and influenced by inflow simulations and RWSC estimates, with NRMSE ranging from 0.09–0.12 and KGE from 0.65–0.74. Based on time-varying Bayesian Model Averaging (BMA) approaches and synthetic aperture radar (SAR) satellite datasets, more accurate inflow and RWSC estimates can be obtained, thus facilitating substantially release estimates. With multi-source satellite datasets, temporal scale of reservoir estimates is increased (monthly and bi-weekly), acting as a key supplement to in situ records. Overall, this study explores the possibility to reconstruct and facilitate reservoir release estimates in poorly gauged dammed basins using hydrological modeling techniques and multi-source satellite datasets.
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