Abstract
On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM) to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL). It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %); and good correlation (CC = 0.9). These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.
Highlights
The understanding of spatial distribution for rainfall, especially during extreme conditions is important for water resources planning, river basin management, hydrological and ecological applications, assessment of groundwater potential, and the design of water supply and irrigation systems [1,2]
Precipitation accumulation for the 6-day duration during rainstorm events is retrieved from TRMM Multi-Satellite Precipitation Analysis (TMPA) 3B42 v7 dataset
An investigation is conducted to determine the suitability of Tropical Rainfall Measuring Mission (TRMM) satellite algorithm estimates to represent the distribution of extreme rainfalls in Sungai Sarawak Basin (SSB)
Summary
The understanding of spatial distribution for rainfall, especially during extreme conditions is important for water resources planning, river basin management, hydrological and ecological applications, assessment of groundwater potential, and the design of water supply and irrigation systems [1,2].In-situ measurements from rain gauge have been implied as the ground truth observations where it yields relatively reliable point records of precipitation [3]. A dense network of rain gauges is required to accurately characterize the variation of rainfall pattern over a region. This is not an ideal condition for areas with a limited network or sparse distribution of gauging and meteorological stations in the tropics, such as in Sarawak, Malaysia. This has resulted to engineering and technological challenges in understanding the spatial distribution of rainfall especially during storm events
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