Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data‐Poor Regions

Sheffield, Justin; Wood, Eric F.; Pan, Ming; Beck, Hylke E.; Coccia, Gabriele; Serrat-Capdevila, Aleix; Verbist, Koen

doi:10.1029/2017wr022437

Cited by 290 publications

(119 citation statements)

References 187 publications

(160 reference statements)

Supporting

Mentioning

113

Contrasting

Unclassified

Order By: Relevance

“…Long-term records are the basis for designing flood control, irrigation and hydropower systems, and transboundary water agreements, while real-time data are needed to operate water infrastructure, and manage and reduce flood and drought risk (García et al 2016;Sheffield et al 2018). They are valuable to make better connections between researchers, policy-makers, and the society for a deeper understanding of the changes that are occurring in our environment due to climate change and anthropogenic activities.…”

Section: Resultsmentioning

confidence: 99%

A global, near real-time system measuring river, lake, and reservoir dynamics

2019

El Sawah, S. (Ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation.

View full text Add to dashboard Cite

Measuring and predicting the dynamics of discharge in rivers and water storage in lakes and reservoirs can inform water management and policy decisions, flood management and response, and help understand the influence of climate change and anthropogenic activities on hydrological, biogeochemical, and ecological processes. However, water body dynamics are often poorly observed on the ground. Gauging networks are unevenly distributed and in decline globally, and much gauging data is not publicly accessible in near real-time, if at all. Remote sensing technologies provide a unique alternative to monitor changes in water extent, level and volume in space and time. Our aim was to develop a global monitoring system that provides near real-time river discharge and lake and reservoir storage information from satellite observations. To estimate river discharge, we derived global surface water extent fraction from the 8-day 0.05° resolution reflectance data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and used recorded discharge at gauged sites and hydrological model estimates at ungauged sites to train MODIS-based satellite gauging reaches (SGRs) that can be used to estimate river discharge globally. In total, we were able to construct over 2,000 gauge-based and 11,000 model-based SGRs globally (Figure 1). To estimate volume changes in lakes and reservoirs, surface water extent dynamics for over 280 lakes and reservoirs (Figure 1) were derived from a daily 500-m resolution global surface water change dataset. Storage variations were calculated using surface water extent and height time series from the 10-day near real-time global lake and reservoir elevation dataset (G-REALM). As MODIS and G-REALM provide near real-time information, these data similarly allow estimation of river discharge and lake and reservoir storage in near real-time. It is hoped that the global monitoring system provides immediate and relevant information on rivers, lakes, and reservoirs, to inform government, the community and individuals on the current state of water resources in a historical context.

show abstract

Section: Resultsmentioning

confidence: 99%

A global, near real-time system measuring river, lake, and reservoir dynamics

2019

El Sawah, S. (Ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation.

View full text Add to dashboard Cite

show abstract

“…Satellite remote sensing is increasingly being used as a complementary source of information to in situ monitoring networks and, in many cases, is the only feasible source [53].…”

Section: Discussionmentioning

confidence: 99%

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Rivera

Hinrichs

Marianetti

2019

Advances in Meteorology

View full text Add to dashboard Cite

e Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987-2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. e large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. e frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. is bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. e results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region.

show abstract

“…In the light of land and water resource management, monitoring of rivers and their entire drainage area is highly important [11]. With more detail, the drainage area of a river, also called river basin, covers all parts of the land surface that contribute to the river discharge at a certain point.…”

Section: Relevance Of River Basinsmentioning

confidence: 99%

“…To our knowledge, there is no review article mainly focusing on EO-based applications in the context of large river basins. However, we identified related reviews e.g., investigating the use of EO in characterizing surface water [14], EO for monitoring river corridors [26], EO for water resources management [11], EO for monitoring flood extent and water level [27], or application of EO in hydrology [28,29]. The overarching objective of this review is to analyze EO-based datasets and their respective spatial and temporal scale.…”

Section: Objectives and Scope Of This Reviewmentioning

confidence: 99%

A Review of Earth Observation-Based Analyses for Major River Basins

Uereyen

Kuenzer

2019

Remote Sensing

View full text Add to dashboard Cite

Regardless of political boundaries, river basins are a functional unit of the Earth’s land surface and provide an abundance of resources for the environment and humans. They supply livelihoods supported by the typical characteristics of large river basins, such as the provision of freshwater, irrigation water, and transport opportunities. At the same time, they are impacted i.e., by human-induced environmental changes, boundary conflicts, and upstream–downstream inequalities. In the framework of water resource management, monitoring of river basins is therefore of high importance, in particular for researchers, stake-holders and decision-makers. However, land surface and surface water properties of many major river basins remain largely unmonitored at basin scale. Several inventories exist, yet consistent spatial databases describing the status of major river basins at global scale are lacking. Here, Earth observation (EO) is a potential source of spatial information providing large-scale data on the status of land surface properties. This review provides a comprehensive overview of existing research articles analyzing major river basins primarily using EO. Furthermore, this review proposes to exploit EO data together with relevant open global-scale geodata to establish a database and to enable consistent spatial analyses and evaluate past and current states of major river basins.

show abstract

Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data‐Poor Regions

Cited by 290 publications

References 187 publications

A global, near real-time system measuring river, lake, and reservoir dynamics

A global, near real-time system measuring river, lake, and reservoir dynamics

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

A Review of Earth Observation-Based Analyses for Major River Basins

Contact Info

Product

Resources

About