International Journal of Water (10 papers in press)
Exploring the certainty of reciprocal relationship with outcome expectations in water conservation efforts among generation Y: social cognitive theory approach
by Ganesh Ramasamy, Rajat Subhra Chatterjee
Abstract: Sustainable water conservation and water management among each individual is a crucial factor for better living standards in the present and future. Even though water supply is generally exercised with a countrys government administration, the conservation of water among the public and their attitude and emotional factors with social cognitive behaviour will play an essential role for present and future generations. In the concentrated context of social cognitive theory, this empirical study were conducted in relation to generation Y in Kuala Lumpur metropolitan city, Malaysia. A sample size of 265 generation Y population was used with convenience sampling method in identifying their attitude and behaviour. The finding revealed that generation Y outcome expectancy has significant positive effect on water conservation. The outcome expectancy was predicted by environmental factors, personal factors and perceived self-efficacy. According to the model evaluation, the adjusted R2 was .78, which explain almost 78% of the variance in outcome expectancy in determining behaviour in water conservation among generation Y in Kuala Lumpur metropolitan city. In reciprocal identifications, the variables were tested with correlation and all variables achieved positive strong correlation.
Keywords: social cognitive theory; reciprocal determinism; water conservation; generation Y; behavioral practice.
Quantitative assessment of climate change impacts on the spatial characteristics of drought hazard in arid and semi-arid regions of Iran
by Jaber Rahimi, Mohammad Khajeh, Abbas Alipour, Ommolbanin Bazrafshan
Abstract: The aim of the present study was to investigate the frequency as well as the spatial extent of meteorological drought hazard in arid and semi-arid regions of Iran for the historical (1985-2010) and future periods (2011-2040, 2041-2070, and 2071-2100) under different RCP scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). For this purpose, monthly precipitation data of 62 synoptic stations, as well as CMIP5 multi-model ensemble projections, were used to calculate the Standard Index Annual Precipitation (SIAP). Next, the percentages of area affected by severe, moderate, and mild droughts in each year were quantified and the Drought Hazard Index (DHI) was obtained based on the frequency of different drought categories. The results demonstrated that for the historical period (1985-2010), the most extensive droughts (severe and moderate) occurred in 2001 (62.84% of the study area), 2008 (43.93% of the study area), and 2010 (45.73% of the study area). Furthermore, projecting future drought conditions revealed that the frequency of severe drought categories is expected to significantly increase and the most extensive and intensive droughts would occur in 2040s under the RCP8.5 scenario (100% of the study area). In addition, drought hazard assessment showed that, by the end of the 21st century (2071-2100), except for a region in the southeastern parts of the study area, the other parts are expected to be categorised as 'very-high-hazard' zones and experience extensive droughts. These changes are important because they would negatively affect agricultural and natural resources in arid and semi-arid regions of Iran.
Keywords: climate change; drought frequency; drought hazard; SIAP.
Sustainable strategies for water management challenges in hill towns
by Sandeep Sharma, Mahua Mukherjee, Deepak Khare
Abstract: Water is the most precious resource on Earth for survival, and its limited. Cities have grown rapidly in recent decades. Besides population, this growth includes additional basic infrastructures such as buildings, roads, waste, and emissions. Increased urbanisation and built infrastructure result in increased runoff due to impermeable surfaces and limited recharging of groundwater, thus causing water scarcity and intensifying water problems in cities, including hill towns. According to the World Health Organization, only 0.007% of the worlds total water supply is safe for consumption. Hill towns are also facing limited access to water. In hill towns, topography plays a major role in the distribution network of water supply. Undulating land profile and the ridges/valleys provide an opportunity for the natural gravitational distribution networks; at the same time, it may create problems for the distribution of water at the right time in the right place with optimal pressure. Wastewater management is also a critical challenge. This study focuses on problems/challenges of water management in hill towns in general. To address the problems holistically, the research is divided into two stages. Stage I focuses on the problems/challenges regarding water management in hill towns, and stage II deals with the scope of improvising the water management supported by the literature at the city level. The paper concludes by suggesting a few possible solutions for sustainable water management to resolve the problems associated with water supply in hill towns. The study will help in achieving sustainable water management in hill towns.
Keywords: sustainable water management; water supply system; water distribution network; hill towns.
Smart rainwater harvesting techniques
by Raseswari Pradhan, Jayaprakash Sahoo
Abstract: In a smart city, the vital factors include smart grid and e-health. Smart city is one of the burning topics of research. Although there is no particular definition of smart city, it means smart grid, e-health, e-environmental monitoring, smart home, smart water quality, smart air quality, etc., integrated into a single application. Human civilisation cant be sustained and prosper with shortage of usable water. Hence, water has a vital share in human life even living in smart cities. This paper describes the smart water quality issues in a smart city and some of the research advances in handling those issues. Among them it investigates the rainwater harvesting technologies and some of their practical applications.
Keywords: rainwater; harvesting technologies; features; traditional methods; rain centres.
Multi-criteria geospatial techniques for selecting potentially suitable sites for aquaculture development in Purba Medinipur, West Bengal, India
by Nirupam Acharyya, Surajit Panda, Swasti Barman, Suman Pratihar, Jatisankar Bandyopadhyay
Abstract: The aquafarming sector has a significant function to produce the fastest food and to maintain the nutritional values as well as the protein requirement for growing populations. Advances in geospatial technology in fish farming site selection assist in spatial distribution, mapping and proper management. This study focuses on the potential and suitable sites of Purba Medinipur district, in India, that were analysed based on two analytical frameworks (a) Site Suitability for Fish Farming (SSFF) and (b) Site Suitability for Commercial Fish Farming (SSCFF). Physicochemical conditions, weather, environment, establishment and profitability were selected as suitability parameters. Spatial interpolation techniques were used to generalise the distribution of water quality (temperature, pH, dissolved oxygen, TDS), soil character (pH, texture), precipitation and population of the fisherfolk families. Proximity and spatial analysis techniques have been adopted to generate the importance scale of perennial river, road-rail network, market, industries, subdivision capital and density (water body, population, etc.), respectively. The distribution of land use and land cover (LULC) and slope from Sentinel-2B and ASTER-DEM has been characterised as another parameter. Weightage overlay analysis has been used to evaluate the distribution of suitable sites. SSFF model shows that 19.91% (77,123.40 ha) area is in suitable, 67.71% (262,351.39 ha) is moderately suitable and 12.38% (47,959.93 ha) areas come under the unsuitable category. Most of the area of Moyna and Bhagawanpur-I blocks come into a suitable zone. The SSCFF model indicated that 12.16% (47,110.05 ha) area is found in a suitable class for the small-scale economically favourable fish farm. The result confirms that the existing situations in the study area support promising opportunities for establishing and developing aquaculture.
Keywords: geospatial technology; water quality; Sentinel-2B; weightage overlay; SSFF-SSCFF; site selection.
Application of support vector machine for river flow estimation
by Hasan Torabi, Reza Dehghani
Abstract: In recent years, the application of intelligent methods has been considered in forecasting hydrological processes. In this research, montlyh river discharge of the Kakareza, a river located in Lorestan province in the west of Iran, was forecast using support vector machine and as genetic programming inference system methods in Dehno stations. In this regard, some different combinations in the period 1979-2015 as input data for estimation of discharge in the monthly index were evaluated. Criteria of correlation coefficient, root mean square error and Nash Sutcliff coefficient to evaluate and compare the performance of methods were used. It showed that a combined structure using surveyed inelegant methods, resulted in an acceptable estimation of discharge to the Kakareza river. In addition, comparison between models shows that support vector machine has a better performance than other models in inflow estimation. In terms of accuracy, support vector machine with correlation coefficients (0.970) has more propriety than root mean square error (0.08m3/s) and Nash Sutcliff (0.94). To sum up, it is mentioned that support vector machine method has a better capability to estimate the minimum, maximum and other flow values.
Keywords: gene expression programming; Kakareza river; support vector machine.
Assessment of global crop yields volatility and its association
with large scale climate, water and temperature variability
by Ehsan Najafi
Abstract: Climate oscillation and local climate variability are vital in determining crop yield volatility, which often results in changes to crop prices. In this study, anomalous spatial and temporal national-based yield values of maize, rice, sorghum and soybean from 1961 to 2013 are extracted using the multivariate statistical procedure of Robust Principal Component Analysis (RPCA). Sea surface temperature anomalies (SSTa), oceanic and atmospheric indices, air temperature anomalies (ATa) and the Palmer Drought Severity Index (PDSI) are used to examine the association between crop yield variability in the most volatile years (MVY). In addition to extreme wet conditions across sorghum croplands in South America, extensive and significant hot or drought patterns are recognised across maize croplands of South America and southern Asia, rice harvesting regions of Oceania and southern Asia, and sorghum and soybean growing regions of North America and southern and southeastern Asia. Results show that warmer-than-normal winter time SSTa (El Ni
Keywords: yield volatility; climate; climate extremes; drought; temperature variability; RPCA.
Impact of land-use change on the hydrological parameters of the watershed: a case study of Hathmati river
by Mohdzuned Shaikh, Pradeep Lodha, Prashant Lalwani
Abstract: The present work deals with assessing the impact of land-use change on a hydrological parameter (evapotranspiration) of a watershed. To demonstrate the work, the Hathmati river, which is one of the most important tributaries of western India, was chosen as the study area. The decadal maps of the year 1985, 1995, 2005 and 2015 have been prepared using the tools mentioned previously, and the SWAT model is prepared to simulate the watershed. The input weather data is obtained from the state government agencies and the spatial data is extracted from CARTOSAT-1. The result shows that with the green cover and agricultural land of the watershed change, the hydrological parameters are affected considerably.
Keywords: land-use change; SWAT; watershed; simulation; evapotranspiration; Hathmati river.
The current situation of water resources and future feasible plans in Taiwan
by YuFen Chen, Ching-Hua Mao
Abstract: Taiwan has been experiencing a shortage of water, and in 2021, Taiwan encountered the most severe drought in the past 56 years. In this study, the researcher mainly explored the current situation, problems, and importance of water resources in Taiwan by citing statistics in the present databases. Through focusing on the unbalanced distribution and shortage of water resources, the researcher probed into the main causes of the water shortage to propose solutions. The researcher attempted to find solutions through the accessibility of water resources, the provision of effective water resources, renewable water resources per capita, and comparisons of water rates in Taiwan with those of other countries.
Keywords: water resources; water shortage; renewable water resources per capita; water rates; Taiwan.
Assessing the impact of meteorological parameters for forecasting floods in the northern districts of Bihar using machine learning
by Vikas Mittal, T.V. Vijay Kumar, Aayush Goel
Abstract: India is the second largest flood-affected country in the world. Every year, floods have a deleterious effect on people, agriculture and infrastructure. Owing to its high population density and poor infrastructure, the damage caused by floods in India is exacerbated thus forcing millions of people to migrate from one place to other. Therefore, there is a need to device flood mitigation strategies that would forecast future floods in real time. In this paper, machine learning techniques have been used for forecasting floods in the northern districts of Bihar. Experimental results showed that, in addition to traditional meteorological parameters rainfall and temperature, certain parameters such as vapour pressure, cloud cover, wet day frequency, crop evapotranspiration and surface evapotranspiration have a severe impact on the performance of a flood-forecasting model.
Keywords: natural hazards; floods; forecasting; artificial intelligence; machine learning; supervised learning; classification.