2020
DOI: 10.3390/app10144885
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Modeling Future Streamflow for Adaptive Water Allocation under Climate Change for the Tanjung Karang Rice Irrigation Scheme Malaysia

Abstract: Spatial and temporal climatic variability influence on the productivity of agricultural watershed and irrigation systems. In a large irrigation system, the quantification and regulation of the flow at different locations of the channel is quite difficult manually, leading to a poor delivery of supply and demand. Water shortage is a crucial issue due to mismatch between available water and demand at intake point of Tanjung-Karang Irrigation Scheme. This study assessed the potential impacts of climate change on … Show more

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Cited by 7 publications
(7 citation statements)
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“…The decision to implement the hydro-amelioration work included in simulation 3 is supported by the comparative analysis of all implemented simulations, being the most viable in terms of implementation-operation costs, as well as in terms of ameliorating impact on the studied ravine [50][51][52].…”
Section: Resultsmentioning
confidence: 99%
“…The decision to implement the hydro-amelioration work included in simulation 3 is supported by the comparative analysis of all implemented simulations, being the most viable in terms of implementation-operation costs, as well as in terms of ameliorating impact on the studied ravine [50][51][52].…”
Section: Resultsmentioning
confidence: 99%
“…The criteria used to select the GCMs are the availability of the latest generation of GCMs, good spatial resolution, past performance of GCM to replicate the historical data and the representativeness of the GCM for a wide range of climatic variable (precipitation) projections [7]. The most commonly adopted criteria are the assessment and selection of GCMs based on their capability to simulate the historical and present climate, which have been adopted by numerous studies [8][9][10]. An efficient and sensible selection of GCMs is required to generate reliable and diverse meteorological inputs for the impact models.…”
Section: Gcm Selectionmentioning
confidence: 99%
“…In this study, the KS test stats were derived as the highest vertical difference between the two cumulative distribution functions (CDFs) of a time series data. For CDF of APHRODITE data ø n (x) and the CDF of the selected GCM or MME mean at a grid station ø (x), the KS test statistics were obtained as given in Equations 7and (8).…”
Section: Kolmogorov-smirnov Testmentioning
confidence: 99%
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“…Addressing of climate change eff ects in the development of hazardous risk adaptation and mitigation plans has been on the agenda of many governments and institutions (Lavell et al, 2012). Hence, eff ective planning requires the examination of both current and projected climate change scenarios (Shrestha at al., 2017).…”
Section: Introductionmentioning
confidence: 99%