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The forecasting of future streamflow aids researchers and policymakers to understand how changes in climate affect hydrological systems. However, traditional computational approaches demand intensive data specifically for the basin, and it is costly. The shift towards more contemporary and data-driven approaches known as support vector regression (SVR) in hydrological modeling utilizing only the hydro-climate data from Coupled Model Intercomparison Project Phase 6 (CMIP6) provides rapid input–output data processing with accurate future projection. CMIP6 is an updated and improved Global Climate Models (GCMs) for the exploration of the specific impacts of changing streamflow patterns for improved water management in agricultural areas. The delta change factor method was used to generate climate sequences, fed into the SVR model to project streamflow from 2021 to 2080. The SVR model fitted reasonably well, demonstrated by several statistical indicators, including Kling-Gupta Efficiency (KGE), Nash–Sutcliffe Efficiency (NSE), Percent Bias (PBias), and Root Mean Squared Error (RMSE), with the training phase performance surpassing the testing phase. Future projections indicated increased rainfall during the dry season for most months, excluding April to June. The rise in precipitation was particularly pronounced during the wet season. Maximum and minimum temperature projections increased for all SSPs, with SSP5-8.5 predicted a substantial increase. The projection revealed that seasonal streamflow changes would range between – 19.1% to – 1.2% and – 7.5% to – 3.1% in the dry and wet seasons, respectively. A considerable streamflow reduction is anticipated for all SSPs in April and May due to increased temperatures, with the most pronounced impact in the SSP5-8.5. Assessing the effects of climate variations on water resource availability is crucial for identifying effective adaptation strategies to address the anticipated rise in irrigation demands due to global warming. The projected streamflow changes due to potential climate impacts are significant for Bukit Merah Reservoir, aiding the formulation of appropriate operational strategies for irrigation releases. [ABSTRACT FROM AUTHOR]

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 basin outflow for 2010–2039, 2040–2069, and 2070–2099 to the baseline period (1976–2005) and used it as input hydrograph to simulate river discharge. A Hydrologic Engineering Corps Hydrologic Modeling System (HEC-HMS) model driven by projections from ten global climate models (GCMs) with three scenarios (Representative Concentration Pathways (RCPs) 4.5, 6.0, and 8.5) used to simulate the outflow and the Hydrologic Engineering Centers River Analysis System (HEC-RAS) model applied for hydraulic modeling. The projected seasonal streamflow showed a decreasing trend for future periods. The average available irrigation supply for historical period is 15.97 m3/s, which would decrease by 12%, 18%, and 21% under RCPs 4.5, 6.0, and 8.5, respectively. Projected irrigation supply showed oversupply and undersupply to the required supply during the growing season. Simulated discharge could therefore be incorporated into cropping practices to boost the sustainable distribution of water under the new realities of climate change in the future. [ABSTRACT FROM AUTHOR]

Hydrological models are reliable tools that have been extensively used for hydrological studies. However, the complexity of some of these models has been a major setback, which affects their performance. This study compared Hydrologic Engineering Corps Hydrologic Modeling System (HEC-HMS) with most widely applied Soil Water Assessment Tool (ArcSWAT) model and used to assess impacts of climate change on streamflow at Bernam Basin, Malaysia for 2010-2039, 2040-2069 and 2070-2099 to the baseline period (1976- 2005) using an ensemble of ten GCMs under three RCP scenarios (RCPs 4.5, 6.0 and 8.5). The models performed satisfactorily. However, HEC-HMS performed better compared to ArcSWAT with 0.74, 0.71, 4.21 and 0.37; and 0.71, 0.69, 5.32 and 0.31 for R2, NSE, PBIAS and RSR, respectively, during the calibration and validation periods. Future periods suggest a decreasing pattern in streamflow, with a higher percentage (−5.94%) expected for the RCP 8.5 scenario in the late century (2080s) during dry season period. In the wet season, streamflow decreases in all future periods except for RCP4.5 where it is expected to increase (0.36%). Therefore, the Basin may likely experience tremendous pressure in the late century due to low streamflow, particularly in dry season months. [ABSTRACT FROM AUTHOR]

Agro-hydrological water management frameworks help to integrate expected planned management and expedite regulation of water allocation for agricultural production. Low production is not only due to the variability of available water during crop growing seasons, but also poor water management decisions. The Tanjung Karang Rice Irrigation Scheme in Malaysia has yet to model agro-hydrological systems for effective water distribution under climate change impacts. A climate-smart agro-hydrological model was developed using Excel-based Visual Basic for Applications (VBA) for adaptive irrigation and wise water resource management towards water security under new climate change realities. Daily climate variables for baseline (1976–2005) and future (2010–2099) periods were extracted from 10 global climate models (GCMs) under three Representative Concentration Pathway scenarios (RCP4.5, RCP6.0, and RCP8.5). The projected available water for supply to the scheme would noticeably decrease during the dry season. The water demand in the scheme will differ greatly during the months in future dry seasons, and the increase in effective rainfall during the wet season will compensate for the high dry season water demand. No irrigation will therefore be needed in the months of May and June. In order to improve water distribution, simulated flows from the model could be incorporated with appropriate cropping patterns. [ABSTRACT FROM AUTHOR]