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 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.

A GIS-Based Spatial Analysis Model Approach for Identification of Optimal Hydrotechnical Solutions for Gully Erosion Stabilization. Case Study

“…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].…”

Application of Machine Learning Techniques to Delineate Homogeneous Climate Zones in River Basins of Pakistan for Hydro-Climatic Change Impact Studies

“…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.…”

“…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).…”

“…Simulation results from general circulation models (GCMs) are used to study the implications of hydro-climatic change and are considered the most comprehensive and valid instruments, with the ability to reproduce climate variables in chronological order as well as yield future projections using scenarios [8][9][10][11] recommended by the intergovernmental panel on climate change (IPCC). Numerous outputs from GCMs are available to gain insight into climate processes and the impact of various scenarios on these processes [12,13].…”

Numerical assessment of climate change impact on the hydrological regime of a small Mediterranean river, Lesvos Island, Greece

“…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).…”