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The purpose of this paper is to simulate and analyze accurately the multi-scale characteristics, variation periods and trends of the annual streamflow series in the Haihe River Basin (HRB) using the Hilbert-Huang Transform (HHT).

The Empirical Mode Decomposition (EMD) approach is adopted to decompose the original signal into intrinsic mode functions (IMFs) in multi-scales. The Hilbert spectrum is applied to each IMF component and the localized time-frequency-energy distribution. The monotonic residues obtained by EMD can be treated as the trend of the original sequence.

The authors apply HHT to 14 hydrological stations in the HRB. The annual streamflow series are decomposed into four IMFs and a residual component, which exhibits the multi-scale characteristics. After the Hilbert transform, the instantaneous frequency, center frequency and mean period of the IMFs are obtained. Common multi-scale periods of the 14 series exist, e.g. 3.3a, 4∼7a, 8∼10a, 11-14a, 24∼25a and 43∼45a. The residues indicate that the annual streamflow series has exhibited a decreasing trend over the past 50 years.

The HHT method is still in its early stages of application in hydrology and needs to be further tested.

It is helpful for the study of the complex features of streamflow.

This paper will contribute to the sustainable utilization of water resources.

This study represents the first use of the HHT method to analyze the multi-scale characteristics of the streamflow series in the HRB. This paper provides an important theoretical support for water resources management.

Climate change is expected to alter the major components of hydrological regime such as streamflow and water availability. The magnitude and their impacts are still uncertain. Therefore, it is highly required to study streamflow and flood vulnerability in tropical river basins particularly urbanised basin such as Langat River Basin. This study aims to model the future streamflow of Langat River Basin due to climate change using Rainfall-Runoff Inundation (RRI) model. Daily rainfall data obtained from Department of Irrigation and Drainage Malaysia and topographic data from HydroSHEDS at 15-second resolution were used. The projected future rainfall (2075–2099) is extracted from MRI-AGCM3.2s under the worst carbon emission scenario, RCP8.5. The annual maximum series of 1-day rainfall is selected for statistical bias correction using Quantile Mapping. The General Circulation Model data were found to be greatly corrected with reasonable Nash–Sutcliffe efficiency, Percent bias and Root Mean Square Error values. The mean of maximum 1-day future rainfall in Langat River Basin is found to be inconsistent where parts of the upstream will experience an increment at about 7% while other parts decrease at 8%. Meanwhile, the rainfall at downstream area are expected to decrease at 40%. Based on RRI simulation, the future streamflow can achieve up to 92% increment.

The purpose of this study is to address a highly heterogeneous rift margin environment and exhibit considerable spatiotemporal hydro-climatic variations. In spite of limited, random and inaccurate data retrieved from rainfall gauging stations, the recent advancement of satellite rainfall estimate (SRE) has provided promising alternatives over such remote areas. The aim of this research is to take advantage of the technologies through performance evaluation of the SREs against ground-based-gauge rainfall data sets by incorporating its applicability in calibrating hydrological models.

Selected multi satellite-based rainfall estimates were primarily compared statistically with rain gauge observations using a point-to-pixel approach at different time scales (daily and seasonal). The continuous and categorical indices are used to evaluate the performance of SRE. The simple scaling time-variant bias correction method was further applied to remove the systematic error in satellite rainfall estimates before being used as input for a semi-distributed hydrologic engineering center's hydraulic modeling system (HEC-HMS). Runoff calibration and validation were conducted for consecutive periods ranging from 1999–2010 to 2011–2015, respectively.

The spatial patterns retrieved from climate hazards group infrared precipitation with stations (CHIRPS), multi-source weighted-ensemble precipitation (MSWEP) and tropical rainfall measuring mission (TRMM) rainfall estimates are more or less comparably underestimate the ground-based gauge observation at daily and seasonal scales. In comparison to the others, MSWEP has the best probability of detection followed by TRMM at all observation stations whereas CHIRPS performs the least in the study area. Accordingly, the relative calibration performance of the hydrological model (HEC-HMS) using ground-based gauge observation (Nash and Sutcliffe efficiency criteria [NSE] = 0.71; R² = 0.72) is better as compared to MSWEP (NSE = 0.69; R² = 0.7), TRMM (NSE = 0.67, R² = 0.68) and CHIRPS (NSE = 0.58 and R² = 0.62).

Calibration of hydrological model using the satellite rainfall estimate products have promising results. The results also suggest that products can be a potential alternative source of data sparse complex rift margin having heterogeneous characteristics for various water resource related applications in the study area.

This research is an original work that focuses on all three satellite rainfall estimates forced simulations displaying substantially improved performance after bias correction and recalibration.

This paper aims to develop a framework to assist the identification of robust adaptation options that account for uncertainty in future climate change impacts for the water sector.

The water evaluation and planning (WEAP) tool, is to identify future water resource vulnerability in the Glore sub‐catchment within the Moy catchment in the West of Ireland. Where water stress is evident, a detailed hydrological modelling approach is developed to enable an assessment of the robustness to uncertainty of future adaptation decisions. WEAP is coupled with a rainfall runoff model (hydrological simulation model), and forced using climate scenarios, statistically downscaled from three global climate models to account for the key sources of uncertainty. While hydrological models are widely applied, they are subject to uncertainties derived from model structure and the parameterisation of the catchment. Here, random sampling of key parameters is employed to incorporate uncertainty from the hydrological modelling process. Behavioural parameter sets are used to generate multiple future streamflow series to determine where the bounds within future hydrological regimes may lie and the ranges within which future adaptation policy pathways need to function.

This framework allows the identification of adaptation options that are robust to uncertainty in future simulations.

Future research will focus on the development of more site‐specific adaptation options including soft and hard adaptation strategies. This approach will be applied to multiple water resource regions within Ireland.

A robust adaptation assessment decreases the risk of expensive and/or mal‐adaptations in a critical sector for society, the economy and the aquatic environment.

This paper seeks to address the issue of persistent and widespread drought conditions during 2000 and 2001, which were the apparent cause of the decline of water levels in the reservoirs of Brazilian hydroelectric power plants.

This issue is addressed here through a case study of the hydroclimatology of the Paraíba river basin, in Southeast Brazil, home to four large multi‐purpose operational reservoirs.

The data analysis shows that neither changes in the frequency nor magnitude of extreme hydrological events (droughts and floods) nor in annual rainfall amounts can be detected from the existing climate record. The explanation is consistent with the fact that the terrestrial water and energy cycles are tightly, and non‐linearly, coupled through evapotranspiration.

Therefore small change in the seasonality of rainfall can have a significant impact on the basin's overall hydrologic regime, and thus on the availability of water resources.

Often, adaptation and resilience to climate variability are discussed in the context of catastrophic events such as floods and droughts. This study suggests that a different type of impacts, those associated with subtle, yet persistent changes of seasonality in the terrestrial water cycle, cannot be ignored in studies of long‐term sustainability of water resources.

This study aims to obtain the mechanistic insights for the fabrication of pure copper thin wall components by selective infrared (IR) laser melting (SLM) and correlated with microstructure development, microhardness, surface morphology and phase analysis. Experimental processes for single track and selection of substrate materials have been studied using a combination of different laser powers and scanning speeds.

SLM of pure copper was performed on a YONGNIAN Laser YLMS-120 SLM machine using an Nd: YAG fiber laser operating at 1,060 nm in the NIR region. Single-track experiments and processing parameters are investigated through different combinations of laser power and scanning speed. The microstructure of the fabricated pure copper samples by SLM technique was analyzed by means of X-ray diffraction, scanning electron microscope equipped with energy disperse spectrometer, optical microscope (OM) and micro-hardness tester.

Steel-based substrates were found suitable for pure copper manufacturing due to sufficient heat accumulation. The width of a single track was determined by liner energy density, showing discontinuities and irregular morphologies at low laser powers and high scanning speeds. As a result of instability of the molten pool induced by Marangoni convection, cracks and cavities were observed to appear along grain boundaries in the microstructure. The top surface morphology of SLM-processed component showed a streamflow structure and irregular shapes. However, the powder particles attached to side surface, which manifest copper powders, are even more sensitive to melt pool of contour track. The crystal phase characteristics of copper components indicated increasing crystallite size of a-Cu, and the decreasing intensity of diffraction peak was attributed to the presence of defects during SLM. The maximum relative density and microhardness were 82 per cent and 61.48 HV0.2, respectively. The minimum thickness of a pure copper thin wall component was 0.2 mm.

This paper demonstrated the forming mechanism and explored feasibility of pure copper thin wall parts by SLM technology in the NIR region. The surface morphology, microstructure and crystal structure were preliminary studied with laser processing parameters.

This paper aims to propose a comprehensive methodology for setting up rural electrifications for indigenous villages with minimum budgets and the lowest possible cost of electricity (COE). The electricity accessibility of rural area in Malaysia is not fully covered and the cost of extending the grid to these areas can be high as RM 2.7m per km. Lack of vigorous policies and economic attraction of the rural areas are also the main barriers to rural electrification. Electricity is an essential element of economic activities and the lack of electricity exacerbates poverty and contributes to its perpetuation. Therefore, a hybrid standalone power system can be an alternative solution for the rural electrification. A hybrid standalone power system is studied to investigate the potential of the implementation and the budget required.

A site survey has been carried out in a village in Peninsular Malaysia, namely, Kampung Ulu Lawin Selatan. A standalone hybrid system is modeled in HOMER Pro software and the data collected from the selected site are used to obtain the system configuration with the lowest COE. The load following and cycle charging energy dispatch methods are compared to identify the optimal system configuration that yields the lowest COE. The diesel generator-only system is chosen as a benchmark for comparisons.

The results show that the hybrid system constituted from the diesel generator, photovoltaic (PV), micro-hydro and energy storage using the load following energy dispatch method yields the lowest COE of RM 0.519 per kWh. The COE of the hybrid system is 378 per cent lower than that of the diesel generator-only system. The lead-acid energy storage system (ESS) is able to reduce 40 per cent of COE as compared to the system without ESS.

The results indicate that the COE of the diesel-micro hydro-PV-ESS system with load following dispatch strategy is RM 0.519 per kWh, and this value is 35 per cent higher than the average electricity price in Malaysia. However, it is important to note that the costs of extending the grid to the rural area are not taken into account. If this cost is considered into the electricity price, then the standalone hybrid power system proposed by this study is still a competitive alternative for rural electrification.

The objective of this study is to propose a functional framework for hydrological applications by treating flood hydrographs as functional data. Discrete flow data are transformed into a smoothing hydrograph curve, which can be analysed at any time interval. The concept of functional data considered the entire curve concerning time as a single observation. This chapter briefly discussed the idea of descriptive statistics, principal components and outliers in a functional framework. These methods were illustrated in the flood study at Sungai Kelantan River Basin, Malaysia. The results showed that five main components accounted for almost 73.8% of the overall flow variance. Based on the results of the factor scores, the hydrograph curves for the years 1988, 1993 and 2014 may be said to have a unique cluster of their own, while the rest of the years which consider having the same pattern. Due to various shapes and magnitudes, the hydrograph curves of 1988 and 2014 are considered outliers. In conclusion, the functional framework has shown that it is capable of representing a wide range of hydrographs and is capable of extracting additional information found in the hydrograph curve that cannot possibly be captured using classical statistical methods.

The upward rise of the prolonged payback period and the inability of the project to generate estimated income that has been linked with the irregular rent payments has been a major problem confronting real estate investment. Given the fact that real estate investment is a risky investment venture with a highly uncertain future stream of income, this paper examines the effectiveness of rent recovery strategies in the emerging Nigeria residential real estate practice.

The study employed an exploratory research design. The study identified the five recovery strategies adopted by the estate surveying and valuation firms in Ibadan Metropolis, Nigeria. The study adopts a purposive sampling method to select 52 registered estate firms in the study area and a questionnaire using a five-point Likert scale was used to elicit information. The data obtained were analyzed using descriptive and inferential statistics.

The result showed that the rent recovery strategies adopted by the respondents include email approach, rent reminder notice, adequate maintenance, eviction notice and dialogue approach. The perceived top-rated strategies that could influence estimated income were dialogue and rent reminder notice. Also, the findings showed the factors that influence the choice of strategy are property type, company policy and the proportion of rent to the tenant's income.

The study has an implication for real estate investors and property practitioners regarding the willingness of the investors to invest in real estate investment.

This paper is relevant given the fact that the rental property market is prone to risk that could impede the regular streamflow of income. This serves as a need for examination of the effectiveness of adopted rent recovery strategies as it relates to real estate property management practice and investment viability.

The purpose of this paper is to provide useful information for members of the weather community and policy makers, to help them understand the full scope of drought economic impacts and assessment methodologies, and to help determine the feasibility of future drought mitigation programs.

To accomplish the objective, the paper reviews the literature of drought economic impact studies in both agricultural and non‐agricultural sectors, summarizes the methods and data employed, compares the various results, and investigates the problems and limitations of previous studies.

The paper concludes with a discussion of the challenges and directions of future improvement on drought economic impact assessment.

This paper gives a comprehensive review of drought economic impacts and the associated quantitative assessment methodologies, which provides valuable information to rational decisions supporting drought mitigation policies and programs.