scholarly journals A daily/25 km short-latency rainfall product for data scarce regions based on the integration of the GPM IMERG Early Run with multiple satellite soil moisture products

2019 ◽  
Author(s):  
Christian Massari ◽  
Luca Brocca ◽  
Thierry Pellarin ◽  
Gab Abramowitz ◽  
Paolo Filippucci ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Resource Management ◽  
Water Resource ◽  
Water Resource Management ◽  
Short Latency ◽  
In Situ Data ◽  
Long Latency ◽  
Agricultural Applications ◽  
Unique Source

Abstract. Rain gauges are unevenly spaced around the world with extremely low gauge density over developing countries. For instance, in some regions in Africa the gauge density is often less than one station per 10 000 km2. The availability of rainfall data provided by gauges is also not always guaranteed in near real time or with a timeliness suited for agricultural and water resource management applications as gauges are also subject to malfunctions and regulations imposed by national authorities. A potential alternative are satellite-based rainfall estimates, yet comparisons with in-situ data suggest they're often not optimal. In this study, we developed a short-latency (i.e., 2–3 days) rainfall product derived from the combination of the Integrated Multi-Satellite Retrievals for GPM early run (IMERG-ER) with multiple satellite soil moisture-based rainfall products derived from ASCAT, SMOS and SMAP L3 satellite soil moisture (SM) retrievals. We tested the performance of this product over four regions characterized by high quality ground-based rainfall datasets (India, Conterminous United States, Australia and Europe) and over data scarce regions in Africa and South America by using Triple Collocation analysis (TC). We found the integration of satellite SM observations with in-situ rainfall observations is very beneficial with improvements of IMERG-ER up to 20 % and 40 % in terms of correlation and error, respectively, and a generalized enhancement in terms of categorical scores with the integrated product often outperforming reanalysis and ground-based long latency datasets. Given the importance of a reliable and readily available rainfall product for water resource management and agricultural applications over data scarce regions, the developed product can provide a valuable and unique source of rainfall information for these regions.

scholarly journals A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products

2020 ◽  
Vol 24 (5) ◽  
pp. 2687-2710 ◽  
Author(s):  
Christian Massari ◽  
Luca Brocca ◽  
Thierry Pellarin ◽  
Gab Abramowitz ◽  
Paolo Filippucci ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Resource Management ◽  
Water Resource ◽  
Water Resource Management ◽  
Short Latency ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Rainfall Estimates

Abstract. Rain gauges are unevenly spaced around the world with extremely low gauge density over developing countries. For instance, in some regions in Africa the gauge density is often less than one station per 10 000 km2. The availability of rainfall data provided by gauges is also not always guaranteed in near real time or with a timeliness suited for agricultural and water resource management applications, as gauges are also subject to malfunctions and regulations imposed by national authorities. A potential alternative is satellite-based rainfall estimates, yet comparisons with in situ data suggest they are often not optimal. In this study, we developed a short-latency (i.e. 2–3 d) rainfall product derived from the combination of the Integrated Multi-Satellite Retrievals for GPM (Global Precipitation Measurement) Early Run (IMERG-ER) with multiple-satellite soil-moisture-based rainfall products derived from ASCAT (Advanced Scatterometer), SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active and Passive) L3 (Level 3) satellite soil moisture (SM) retrievals. We tested the performance of this product over four regions characterized by high-quality ground-based rainfall datasets (India, the conterminous United States, Australia and Europe) and over data-scarce regions in Africa and South America by using triple-collocation (TC) analysis. We found that the integration of satellite SM observations with in situ rainfall observations is very beneficial with improvements of IMERG-ER up to 20 % and 40 % in terms of correlation and error, respectively, and a generalized enhancement in terms of categorical scores with the integrated product often outperforming reanalysis and ground-based long-latency datasets. We also found a relevant overestimation of the rainfall variability of GPM-based products (up to twice the reference value), which was significantly reduced after the integration with satellite soil-moisture-based rainfall estimates. Given the importance of a reliable and readily available rainfall product for water resource management and agricultural applications over data-scarce regions, the developed product can provide a valuable and unique source of rainfall information for these regions.

A review of the methods available for estimating soil moisture and its implications for water resource management

2012 ◽  
Vol 458-459 ◽  
pp. 110-117 ◽  
Author(s):  
Pariva Dobriyal ◽  
Ashi Qureshi ◽  
Ruchi Badola ◽  
Syed Ainul Hussain
Keyword(s):  
Soil Moisture ◽  
Resource Management ◽  
Water Resource ◽  
Water Resource Management

Water Resource Management

2022 ◽  
pp. 197-218
Author(s):  
Satya Prakash ◽  
Pinakana Sai Deepak
Keyword(s):  
Big Data ◽  
Resource Management ◽  
Water Resource ◽  
Water Resource Management ◽  
Satellite Images ◽  
Measurement Techniques ◽  
Satellite Image ◽  
Quality Parameters ◽  
In Situ Measurement

Water is an essential component for the survival of mankind and for balancing the ecosystem and livelihood. The world is experiencing a scarcity of water, both in terms of quality and quantity. Although there are several in-situ measurement techniques, they seem insufficient for large areas involving several parameters. Analysis of satellite images for estimating the quality and quantity of natural water has become an accepted tool for better spatial planning. With the increase in variety, volume, and velocity of satellite image, a tool for faster and accurate processing of the data is needed. Google Earth Engine (GEE) is one such cloud-based geo-big data platform. This chapter reviews the work of several researchers worldwide who have used and demonstrated the capability of satellite images with other geo-big data such as elevation, landcover, etc. for water resource management on the GEE platform. It can be concluded from the review work that GEE can help in estimating the water quality parameters with reasonable accuracy, comparable to the in-situ measurement, albeit quickly.

Catchment surveillance for water resource management

Waterlines ◽  
1997 ◽  
Vol 16 (1) ◽  
pp. 23-25
Author(s):  
Barry Lloyd ◽  
Teresa Thorpe
Keyword(s):  
Resource Management ◽  
Water Resource ◽  
Water Resource Management

Water Resources Management in the Semi-Arid Central Valley of California

1987 ◽  
Vol 19 (9) ◽  
pp. 97-106
Author(s):  
J. J. Vasconcelos
Keyword(s):  
Resource Management ◽  
Ground Water ◽  
Water Resource ◽  
Water Resource Management ◽  
Arid Regions ◽  
Central Valley ◽  
The United States ◽  
Policy Makers ◽  
Ground Water Resource ◽  
Semi Arid

Hater resource managers in semi-arid regions are faced with some unique problems. The wide variations in precipitation and stream flows in semi-arid regions increase man's dependence on the ground water resource for an ample and reliable supply of water. Proper management of the ground water resource is absolutely essential to the economic well being of semi-arid regions. Historians have discovered the remains of vanished advanced civilizations based on irrigated agriculture which were ignorant of the importance of proper ground water resource management. In the United States a great deal of effort is presently being expended in the study and control of toxic discharges to the ground water resource. What many public policy makers fail to understand is that the potential loss to society resulting from the mineralization of the ground water resource is potentially much greater than the loss caused by toxic wastes discharges, particularly in developing countries. Appropriations for ground water resource management studies in developed countries such as the United States are presently much less than those for toxic wastes management and should be increased. It is the reponsibility of the water resource professional to emphasize to public policy makers the importance of ground water resource management. Applications of ground water resource management models in the semi-arid Central Valley of California are presented. The results demonstrate the need for proper ground water resource management practices in semi-arid regions and the use of ground water management models as a valuable tool for the water resource manager.

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