Browsing by Autor "Yawar Hussain"

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Comparative Assessments of the Latest GPM Mission’s Spatially Enhanced Satellite Rainfall Products over the Main Bolivian Watersheds
(Multidisciplinary Digital Publishing Institute, 2017) Frédéric Satgé; Alvaro Xavier; Ramiro Pillco Zolá; Yawar Hussain; F. Timouk; Jérémie Garnier; Marie‐Paule Bonnet
The new IMERG and GSMaP-v6 satellite rainfall estimation (SRE) products from the Global Precipitation Monitoring (GPM) mission have been available since January 2015. With a finer grid box of 0.1°, these products should provide more detailed information than their latest widely-adapted (relatively coarser spatial scale, 0.25°) counterpart. Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) assessment is done by comparing their rainfall estimations with 247 rainfall gauges from 2014 to 2016 in Bolivia. The comparisons were done on annual, monthly and daily temporal scales over the three main national watersheds (Amazon, La Plata and TDPS), for both wet and dry seasons to assess the seasonal variability and according to different slope classes to assess the topographic influence on SREs. To observe the potential enhancement in rainfall estimates brought by these two recently released products, the widely-used TRMM Multi-satellite Precipitation Analysis (TMPA) product is also considered in the analysis. The performances of all the products increase during the wet season. Slightly less accurate than TMPA, IMERG can almost achieve its main objective, which is to ensure TMPA rainfall measurements, while enhancing the discretization of rainy and non-rainy days. It also provides the most accurate estimates among all products over the Altiplano arid region. GSMaP-v6 is the least accurate product over the region and tends to underestimate rainfall over the Amazon and La Plata regions. Over the Amazon and La Plata region, SRE potentiality is related to topographic features with the highest bias observed over high slope regions. Over the TDPS watershed, the high rainfall spatial variability with marked wet and arid regions is the main factor influencing SREs.
Reliability of <scp>SM2RAIN</scp> precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions
(Wiley, 2020) Frédéric Satgé; Yawar Hussain; Jorge Molina‐Carpio; Ramiro Pillco Zolá; Coralie Laugner; Gulraiz Akhter; Marie‐Paule Bonnet
Abstract Numerous satellite‐based precipitation datasets have been successively made available. Their precipitation estimates rely on clouds properties derived from microwave and thermal sensors in a so‐named ‘top‐down’ approach. Recently, a ‘bottom‐up’ approach to infer precipitation from soil moisture (SM) estimates has resulted in the release of two new precipitation datasets (P‐datasets). One uses satellite‐based SM estimates from the European Spatial Agency (ESA) Climate Change Initiative (CCI) (SM2RAIN‐CCI) while the other uses satellite‐based SM from European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Advanced SCATterometer (ASCAT) (SM2RAIN‐ASCAT). This study assesses SM2RAIN‐ASCAT and ‐CCI reliability over two arid regions: Bolivian and Peruvian Altiplano and Pakistan (South Asia) using (a) direct comparisons with rain gauges and (b) testing the sensitivity of streamflow modelling to the P‐datasets. Selecting two different regions and different indicators helps to assess whether the P‐dataset reliability varies depending on the assessment method and location. For comparison purposes, the most reliable P‐datasets from the literature are also considered (IMERG‐E v.6, IMERG‐L v.6, IMERG‐F v.6, CHIRPS v.2 and MSWEP v.2.2). Compared to rain gauge observations and based on the modified Kling–Gupta Efficiency (KGE) values, the SM2RAIN‐ASCAT and ‐CCI are more accurate in the Altiplano than in Pakistan. This difference is explained by a more favourable physical context for satellite‐based SM estimates in the Altiplano. Over the Altiplano and despite an overall positive bias, SM2RAIN‐ASCAT describes rain gauges temporal dynamics as well as IMERG‐F v.6, CHIRPS v.2 and MSWEP v.2.2 and provides streamflow simulations very close to those obtained when using IMERG‐F v.6, CHIRPS v.2 and MSWEP v.2.2 as forcing data.
Unraveling the impacts of droughts and agricultural intensification on the Altiplano water resources
(Elsevier BV, 2019) Frédéric Satgé; Yawar Hussain; Alvaro Xavier; Ramiro Pillco Zolá; Leandro de Almeida Salles; F. Timouk; F. Seyler; Jérémie Garnier; Frédéric Frappart; Marie‐Paule Bonnet