scholarly journals Evaluasi Kesesuaian Data Satelit untuk Curah Hujan dan Evaporasi Terhadap Data Pengukuran di Kawasan Waduk Sutami

2021 ◽  
Vol 1 (2) ◽  
pp. 904-916
Author(s):  
Naufal Achmad Arrokhman ◽  
◽  
Sri Wahyuni ◽  
Ery Suhartanto ◽  
◽  
...  
Keyword(s):  
Trmm 3B42

Waduk Sutami merupakan waduk multiguna sehingga diperlukan pencatatan data curah hujan maupun data evaporasi yang lengkap sebagai dasar mengatur pola operasi waduk, analisis neraca air, dan lain-lain. Seiring perkembangan zaman, teknologi satelit dapat digunakan sebagai alternatif data hidrologi untuk mengantisipasi ketidaklengkapan dan ketidak-akuratan data saat pengukuran. Tujuan dari penelitian ini untuk melakukan evaluasi data satelit curah hujan dan evaporasi terhadap data pengukuran di Kawasan Waduk Sutami. Dari penelitian ini juga akan menghasilkan satelit yang direkomendasikan untuk dapat diterapkan pada lokasi studi. Dalam penelitian ini, penulis menggunakan data satelit curah hujan TRMM 3B42, CHIRPS, dan GPM V6. Sedangkan satelit evaporasi menggunakan GLDAS-2.1 dan CFS-V2. Masing-masing satelit tersebut mempunyai spesifikasi dan karakteristik yang berbeda-beda. Evaluasi data satelit dilakukan dengan menggunakan simulasi model kalibrasi dan validasi untuk mengetahui performa dari satelit tersebut. Hasil yang terbaik dapat diketahui dari nilai RMSE, NSE, Koefisien Korelasi, dan Kesalahan Relatif. Hasil penelitian menunjukkan bahwa pada intinya, seluruh satelit curah hujan (TRMM 3B42, CHIRPS, GPM V6) maupun satelit evaporasi (GLDAS-2.1, CFSV2) dapat digunakan sebagai alternatif data hidrologi di Kawasan Waduk Sutami. Hanya saja satelit curah hujan GPM V6 dan satelit evaporasi CFS-V2 memiliki tingkat keakurasian yang lebih tinggi dan performa yang lebih baik berdasarkan simulasi kalibrasi dan validasi.

scholarly journals Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013)

2018 ◽  
Vol 10 (12) ◽  
pp. 1879 ◽  
Author(s):  
Véronique Michot ◽  
Daniel Vila ◽  
Damien Arvor ◽  
Thomas Corpetti ◽  
Josyane Ronchail ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial Coverage ◽  
Rainfall Regimes ◽  
Trmm 3B42 ◽  
Good Agreement

Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

scholarly journals Evaluation and Hydrologic Validation of Three Satellite-Based Precipitation Products in the Upper Catchment of the Red River Basin, China

2018 ◽  
Vol 10 (12) ◽  
pp. 1881 ◽  
Author(s):  
Yueyuan Zhang ◽  
Yungang Li ◽  
Xuan Ji ◽  
Xian Luo ◽  
Xue Li
Keyword(s):  
River Basin ◽  
Southwest China ◽  
Spatial Scales ◽  
Red River ◽  
Low Flow ◽  
Efficiency Coefficient ◽  
Monthly Streamflow ◽  
Red River Basin ◽  
Hydrological Applications ◽  
Trmm 3B42

Satellite-based precipitation products (SPPs) provide alternative precipitation estimates that are especially useful for sparsely gauged and ungauged basins. However, high climate variability and extreme topography pose a challenge. In such regions, rigorous validation is necessary when using SPPs for hydrological applications. We evaluated the accuracy of three recent SPPs over the upper catchment of the Red River Basin, which is a mountain gorge region of southwest China that experiences a subtropical monsoon climate. The SPPs included the Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 product, the Climate Prediction Center (CPC) Morphing Algorithm (CMORPH), the Bias-corrected product (CMORPH_CRT), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Climate Data Record (PERSIANN_CDR) products. SPPs were compared with gauge rainfall from 1998 to 2010 at multiple temporal (daily, monthly) and spatial scales (grid, basin). The TRMM 3B42 product showed the best consistency with gauge observations, followed by CMORPH_CRT, and then PERSIANN_CDR. All three SPPs performed poorly when detecting the frequency of non-rain and light rain events (<1 mm); furthermore, they tended to overestimate moderate rainfall (1–25 mm) and underestimate heavy and hard rainfall (>25 mm). GR (Génie Rural) hydrological models were used to evaluate the utility of the three SPPs for daily and monthly streamflow simulation. Under Scenario I (gauge-calibrated parameters), CMORPH_CRT presented the best consistency with observed daily (Nash–Sutcliffe efficiency coefficient, or NSE = 0.73) and monthly (NSE = 0.82) streamflow. Under Scenario II (individual-calibrated parameters), SPP-driven simulations yielded satisfactory performances (NSE >0.63 for daily, NSE >0.79 for monthly); among them, TRMM 3B42 and CMORPH_CRT performed better than PERSIANN_CDR. SPP-forced simulations underestimated high flow (18.1–28.0%) and overestimated low flow (18.9–49.4%). TRMM 3B42 and CMORPH_CRT show potential for use in hydrological applications over poorly gauged and inaccessible transboundary river basins of Southwest China, particularly for monthly time intervals suitable for water resource management.

Integrated spatiotemporal trends using TRMM 3B42 data for the Upper São Francisco River basin, Brazil

2018 ◽  
Vol 190 (3) ◽  
Author(s):  
Celso Augusto Guimarães Santos ◽  
Reginaldo Moura Brasil Neto ◽  
Richarde Marques da Silva ◽  
Jacqueline Sobral de Araújo Passos
Keyword(s):  
River Basin ◽  
Sao Francisco River ◽  
Spatiotemporal Trends ◽  
São Francisco River ◽  
Trmm 3B42

Ground validation of diurnal TRMM 3B42 V7 and GPM precipitation products over the northeast of Iran

2020 ◽  
Vol 142 (3-4) ◽  
pp. 1413-1423
Author(s):  
Zahra Shirmohammadi-Aliakbarkhani ◽  
Abolghasem Akbari
Keyword(s):  
Ground Validation ◽  
Trmm 3B42

scholarly journals The Impact of Concave Coastline on Rainfall Offshore Distribution over Indonesian Maritime Continent

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Furqon Alfahmi ◽  
Rizaldi Boer ◽  
Rahmat Hidayat ◽  
Perdinan ◽  
Ardhasena Sopaheluwakan
Keyword(s):  
Rainfall Intensity ◽  
Land Breeze ◽  
Convergence Zone ◽  
Maritime Continent ◽  
Low Level ◽  
The North ◽  
The World ◽  
The Impact ◽  
Support Activity ◽  
Trmm 3B42

Indonesian Maritime Continent has the second longest coastline in the world, but the characteristics of offshore rainfall and its relation to coastline type are not clearly understood. As a region with eighty percent being an ocean, knowledge of offshore rainfall is important to support activity over oceans. This study investigates the climatology of offshore rainfall based on TRMM 3B42 composite during 1998-2015 and its dynamical atmosphere which induces high rainfall intensity using WRF-ARW. The result shows that concave coastline drives the increasing rainfall over ocean with Cenderawasih Bay (widest concave coastline) having the highest rainfall offshore intensity (16.5 mm per day) over Indonesian Maritime Continent. Monthly peak offshore rainfall over concave coastline is related to direction of concave coastline and peak of diurnal cycle influenced by the shifting of low level convergence. Concave coastline facing the north has peak during northwesterly monsoonal flow (March), while concave coastline facing the east has peak during easterly monsoonal flow (July). Low level convergence zone shifts from inland during daytime to ocean during nighttime. Due to shape of concave coastline, land breeze strengthens low level convergence and supports merging rainfall over ocean during nighttime. Rainfall propagating from the area around inland to ocean is approximately 5.4 m/s over Cenderawasih Bay and 4.1 m/s over Tolo Bay. Merger rainfall and low level convergence are playing role in increasing offshore rainfall over concave coastline.

scholarly journals Suitability of TRMM Products with Different Temporal Resolution (3-Hourly, Daily, and Monthly) for Rainfall Erosivity Estimation

2020 ◽  
Vol 12 (23) ◽  
pp. 3924
Author(s):  
Xianghu Li ◽  
Zhen Li ◽  
Yaling Lin
Keyword(s):  
Temporal Resolution ◽  
Tropical Rainfall Measuring Mission ◽  
Relative Bias ◽  
Rainfall Erosivity ◽  
Lake Basin ◽  
Monthly Data ◽  
Poyang Lake Basin ◽  
Spatial Performance ◽  
Annual Scale ◽  
Trmm 3B42

Rainfall erosivity (RE) is a significant indicator of erosion capacity. The application of Tropical Rainfall Measuring Mission (TRMM) rainfall products to deal with RE estimation has not received much attention. It is not clear which temporal resolution of TRMM data is most suitable. This study quantified the RE in the Poyang Lake basin, China, based on TRMM 3B42 3-hourly, daily, and 3B43 monthly rainfall data, and investigated their suitability for estimating RE. The results showed that TRMM 3-hourly product had a significant systematic underestimation of monthly RE, especially during the period of April–June for the large values. The TRMM 3B42 daily product seems to have better performance with the relative bias of 3.0% in summer. At the annual scale, TRMM 3B42 daily and 3B43 monthly data had acceptable accuracy, with mean error of 1858 and −85 MJ∙mm/ha∙h and relative bias of 18.3% and −0.85%, respectively. A spatial performance analysis showed that all three TRMM products generally captured the overall spatial patterns of RE, while the TRMM 3B43 product was more suitable in depicting the spatial characteristics of annual RE. This study provides valuable information for the application of TRMM products in mapping RE and risk assessment of soil erosion.

scholarly journals Systematic Evaluation of Satellite-Based Rainfall Products over the Brahmaputra Basin for Hydrological Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Sagar Ratna Bajracharya ◽  
Wahid Palash ◽  
Mandira Singh Shrestha ◽  
Vijay Ratan Khadgi ◽  
Chu Duo ◽  
...  
Keyword(s):  
Water Resources ◽  
Absolute Error ◽  
Rain Gauge ◽  
Systematic Evaluation ◽  
Flood Prediction ◽  
Verification Methods ◽  
Satellite Rainfall ◽  
Data Gap ◽  
Warning Services ◽  
Trmm 3B42

Estimation of the flow generated in the Brahmaputra river basin is important for establishing an effective flood prediction and warning services as well as for water resources assessment and management. But this is a data scarce region with few and unevenly distributed hydrometeorological stations. Five high-resolution satellite rainfall products (CPC RFE2.0, RFE2.0-Modified, CMORPH, GSMaP, and TRMM 3B42) were evaluated at different spatial and temporal resolutions (daily, dekadal, monthly, and seasonal) with observed rain gauge data from 2004 to 2006 to determine their ability to fill the data gap and suitability for use in hydrological and water resources management applications. Grid-to-grid (G-G) and catchment-to-catchment (C-C) comparisons were performed using the verification methods developed by the International Precipitation Working Group (IPWG). Comparing different products, RFE2.0-Modified, TRMM 3B42, and CMORPH performed best; they all detected heavy, moderate, and low rainfall but still significantly underestimated magnitude of rainfall, particularly in orographically influenced areas. Overall, RFE2.0-Modified performed best showing a high correlation coefficient with observed data and low mean absolute error, root mean square error, and multiple bias and is reasonably good at detecting the occurrence of rainfall. TRMM 3B42 showed the second best performance. The study demonstrates that there is a potential use of satellite rainfall in a data scarce region.

An observation-based approach for global runoff estimation: exploiting satellite soil moisture and Grace

2020 ◽  
Author(s):  
Stefania Camici ◽  
Luca Brocca ◽  
Christian Massari ◽  
Gabriele Giuliani ◽  
Nico Sneeuw ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Storage ◽  
Data Access ◽  
Satellite Observations ◽  
Terrestrial Water Storage ◽  
Total Runoff ◽  
The World ◽  
Terrestrial Water ◽  
Trmm 3B42

&lt;p&gt;Water is at the centre of economic and social development; it is vital to maintain health, grow food, manage the environment, produce renewable energy, support industrial processes and create jobs. Despite the importance of water, to date over one third of the world's population still lacks access to drinking water resources and this number is expected to increase due to climate change and outdated water management. As over half of the world&amp;#8217;s potable water supply is extracted from rivers, either directly or from reservoirs, understanding the variability of the stored water on and below landmasses, i.e., runoff, is of primary importance. Apart from river discharge observation networks that suffer from many known limitations (e.g., low station density and often incomplete temporal coverage, substantial delay in data access and large decline in monitoring capacity), runoff can be estimated through model-based or observation-based approaches whose outputs can be highly model or data dependent and characterised by large uncertainties.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;On this basis, developing innovative methods able to maximize the recovery of information on runoff contained in current satellite observations of climatic and environmental variables (i.e., precipitation, soil moisture, terrestrial water storage anomalies and land cover) becomes mandatory and urgent. In this respect, within the European Space Agency (ESA) STREAM Project (SaTellite based Runoff Evaluation And Mapping), a solid &amp;#8220;observational&amp;#8221; approach, exploiting space-only observations of Precipitation (P), Soil Moisture (SM) and Terrestrial Water Storage Anomalies (TWSA) to derive total runoff has been developed and validated. Different P and SM products have been considered. For P, both in situ and satellite-based (e.g., Tropical Rainfall Measuring Mission, TRMM 3B42) datasets have been collected; for SM, Advanced SCATterometer, ASCAT, and ESA Climate Change Initiative, ESA CCI, soil moisture products have been extracted. TWSA time series are obtained from the latest Goddard Space Flight Center&amp;#8217;s global mascon model, which provides storage anomalies and their uncertainties in the form of monthly surface mass densities per approximately 1&amp;#176;x1&amp;#176; blocks.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Total runoff estimates have been simulated for the period 2003-2017 at 5 pilot basins across the world (Mississippi, Amazon, Niger, Danube and Murray Darling) characterised by different physiographic/climatic features. Results proved the potentiality of satellite observations to estimate runoff at daily time scale and at spatial resolution better than GRACE spatial sampling. In particular, by using satellite TRMM 3B42 rainfall data and ESA CCI soil moisture data, very good runoff estimates have been obtained over Amazon basin, with a Kling-Gupta efficiency (KGE) index greater than 0.92 both at the closure and over several inner stations in the basin. Good results found for Mississippi and Danube are also encouraging with KGE index greater than 0.75 for both the basins.&lt;/p&gt;

Snow-Hydrological modeling using remote sensing data in Vilcanota basin, Peru

2020 ◽  
Author(s):  
Eber Risco ◽  
Waldo Lavado ◽  
Pedro Rau
Keyword(s):  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Time Consistency ◽  
Rain Gauge ◽  
Rainfall Runoff ◽  
Direct Evaluation ◽  
Daily Discharge ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Trmm 3B42

&lt;p&gt;Water resources availability in the southern Andes of Peru is being affected by glacier and snow retreat. This problem is already perceived in the Vilcanota river basin, where hydro-climatological information is scarce. In this particular mountain context, any water plan represents a great challenge. To cope with these limitations, we propose to assess the space-time consistency of 10 satellite-based precipitation products (CMORPH&amp;#8211;CRT v.1, CMORPH&amp;#8211;BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, GSMaP correction, MSWEP v.2.1, PERSIANN, PERSIANN&amp;#8211;CDR, TRMM 3B42) with 25 rain gauge stations in order to select the best product that represents the variability in the Vilcanota basin. For this purpose, through a direct evaluation of sensitivity analysis via the GR4J parsimonious hydrological model over the basin. GSMap v.6, TRMM 3B42 and CHIRPS were selected to represent rainfall spatial variability according with different statistical criteria, such as correlation coefficient (CC), standard deviation (SD), percentage of bias (%B) and centered mean square error (CRMSE). To facilitate the interpretation of statistical results, Taylor's diagram was used to represent the CC statistics, normalized values of SD and CRMSE.&lt;/p&gt;&lt;p&gt;A distributed degree-day model was chosen to analyse the sensitivity of snow cover simulations and hydrological contribution. The GR4J rainfall-runoff model was calibrated (using global optimization) and applied to simulate the daily discharge and compared with the Distributed Hydrology and Vegetation Model with Glacier Dynamics (DHSVM-GDM) over the 2001-2018 period. Furthermore, the simulated streamflow was evaluated through comparisons with observations at the hydrological stations using Nash&amp;#8211;Sutcliffe efficiency and Kling Gupta Efficiency (KGE). The results show that the snow-runoff have increased in recent years, so new water management and planning strategies should be developed in the basin. This research is part of the multidisciplinary collaboration between British and Peruvian scientists (Newton Fund, Newton-Paulet) through RAHU project.&lt;/p&gt;

Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia

2017 ◽  
Vol 187 ◽  
pp. 95-105 ◽  
Author(s):  
Kiyoung Kim ◽  
Jongmin Park ◽  
Jongjin Baik ◽  
Minha Choi
Keyword(s):  
East Asia ◽  
Far East ◽  
Trmm 3B42
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