Your search found 20 records
1 Gonima, L.; Gomez, E. C. 1996. Distrito de Riego Samaca Boyaca - Evaluacion ambiental diagnostico sanitario. In Spanish. [Environmental evaluation, sanitary diagnosis - Boyaca Samac Irrigation District]. Medellin, Colombia: International Irrigation Management Institute (IIMI); Medellin, Colombia: International Center for Tropical Agriculture (CIAT). 64p.
(Location: IWMI HQ Call no: IIMI 631.7 G518 GON Record No: H019418)
2 Kerry, R.; Oliver, M. A. 2004. Average variograms to guide soil sampling. International Journal of Applied Earth Observation and Geoinformation, 5(4):307-325.
(Location: IWMI-HQ Call no: P 7330 Record No: H036910)
(Location: IWMI-HQ Call no: IWMI 333.91 G430 BOS Record No: H038187)
4 Fink, A. (Ed.) 2003. The survey kit. Vol.7. How to sample in surveys, by A. Fink. 2nd ed. Thousand Oaks, CA, USA: Sage. 75p. (Survey Kit)
(Location: IWMI-HQ Call no: 300.723 G000 SUR Record No: H039091)
5 Poate, C. D.; Daplyn, P. F. 1993. Data for agrarian development. New York, USA: Cambridge University Press. 387p. (WYE Studies in Agricultural and Rural Development)
(Location: IWMI-HQ Call no: 338.1 G000 POA Record No: H041132)
Call no: e-copy only Record No: H041501)
(Location: IWMI HQ Call no: e-copy only Record No: H042066)
(1.19 MB)
8 Boelee, Eline; Senzanje, A.; Munamati, M.; Parron, L.; Rodrigues, L.; Laamrani, Hammou; Cecchi, P. 2009. Water quality assessment. In Andreini, Marc; Schuetz, Tonya; Harrington, Larry (Eds.). Small reservoirs toolkit, theme 3: ecosystems and health. Colombo, Sri Lanka: CGIAR Challenge Program on Water and Food (CPWF); Colombo, Sri Lanka: International Water Management Institute (IWMI); Brasilia, DF, Brasil: Brazilian Agricultural Research Corporation (Embrapa Cerrados Center); Harare, Zimbabwe: University of Zimbabwe (UZ); Accra, Ghana: Ghana Water Research Institution (WRI); Delft, The Netherlands: Delft University of Technology (TUD); Stockholm, Sweden: Stockholm Environment Institute (SEI); Marseille, France: Institut de Recherche pour le Developpement (IRD); Bonn, Germany: Center for Development Research, University of Bonn; Ithaca, NY, USA: Cornell University. 13p.
(Location: IWMI HQ Call no: e-copy only Record No: H042670)
Some rural populations are dependent on small reservoirs for their water supply and are concerned about the quality of this water for direct consumption and other uses. Chemical and biological water quality measurements can be made to ascertain the suitability of water for different uses. Water “suitability” of course, depends on the use for which it is intended. This tool describes selected methods for assessing the suitability of reservoir water quality.
9 Barry, K.; Vanderzalm, J.; Pavelic, Paul; Regel, R.; May, R.; Dillon, P.; Sidhu, J.; Levett, K. 2010. Bolivar Reclaimed Water Aquifer Storage and Recovery Project: assessment of the third and fourth ASR cycles. Collingwood, VIC, Australia: CSIRO. Water for a Healthy Country National Research Flagship. 111p. (Water for a Healthy Country Flagship Report Series)
(Location: IWMI HQ Call no: e-copy only Record No: H043733)
(3.62 MB) (3.61 MB)
10 Hem, J. D. 1978. Study and interpretation of the chemical characteristics of natural water. 2nd ed. Washington, DC, USA: US Geological Survey. 363p. + fold. map. (Geological Survey Water Supply Paper 1473)
(Location: IWMI HQ Call no: 333.91 G000 HEM Record No: H043952)
(0.56 MB)
(Location: IWMI HQ Call no: 631.4 G000 BLA Record No: H043954)
(0.49 MB)
12 Stalnacke, P.; Tesfai, M.; Kakumanu, Krishna Reddy. 2012. Water quality trends in the Manjeera River, Godavari Basin. [India]. In Nagothu, U. S.; Gosain, A. K.; Palanisami, Kuppannan (Eds.). Water and climate change: an integrated approach to address adaptation challenges. New Delhi, India: Macmillan. pp.123-142.
(Location: IWMI HQ Call no: IWMI Record No: H044766)
(1.35 MB)
(Location: IWMI HQ Call no: 610.72 G000 BOR Record No: H044937)
(0.48 MB)
(Location: IWMI HQ Call no: e-copy only Record No: H045012)
(0.48 MB)
Assessment was done of heavy-metal contamination and its related health risks in urban vegetable farming in Accra. Samples of irrigation water (n = 120), soil (n = 144) and five different kinds of vegetable (n = 240) were collected and analyzed for copper, zinc, lead, cadmium, chromium, nickel and cobalt. All water, soil and vegetable samples contained detectable concentrations of each of the seven heavy metals except for irrigation water which had no detectable chromium, cadmium and cobalt. All heavy-metal levels were below permissible limits except lead on vegetables which was 1.8–3.5 times higher. Health risk assessments showed for all elements that normal consumption of each of the vegetables assessed poses no risk. The highest hazard index obtained was 42 % for wastewater irrigated cabbage. Though within permissible limits, cabbage and ayoyo had the highest potential risk. Compared with previous studies on the same sites, the data show that the risk from heavy metals is less significance than that from pathogen contamination which has positive implications for risk mitigation.
15 Kumar, R. 1996. Research methodology: a step-by-step guide for beginners. South Melbourne, Australia: Addison Wesley Longman Australia. 276p.
(Location: IWMI HQ Call no: 001.42 G000 KUM Record No: H046482)
(0.46 MB)
(Location: IWMI HQ Call no: 363.728 G000 STR Record No: H046586)
(0.65 MB)
(Location: IWMI HQ Call no: e-copy only Record No: H048177)
Chronic kidney disease of unknown (“u”) cause (CKDu) is a growing public health concern in Sri Lanka. Prior research has hypothesized a link with drinking water quality, but rigorous studies are lacking. This study assesses the relationship between nephrotoxic elements (namely arsenic (As), cadmium (Cd), lead (Pb), and uranium (U)) in drinking water, and urine samples collected from individuals with and/or without CKDu in endemic areas, and from individuals without CKDu in nonendemic areas. All water samples – from a variety of source types (i.e. shallow and deep wells, springs, piped and surface water) – contained extremely low concentrations of nephrotoxic elements, and all were well below drinking water guideline values. Concentrations in individual urine samples were higher than, and uncorrelated with, those measured in drinking water, suggesting potential exposure from other sources. Mean urinary concentrations of these elements for individuals with clinically diagnosed CKDu were consistently lower than individuals without CKDu both in endemic and nonendemic areas. This likely stems from the inability of the kidney to excrete these toxic elements via urine in CKDu patients. Urinary concentrations of individuals were also found to be within the range of reference values measured in urine of healthy unexposed individuals from international biomonitoring studies, though these reference levels may not be safe for the Sri Lankan population. The results suggest that CKDu cannot be clearly linked with the presence of these contaminants in drinking water. There remains a need to investigate potential interactions of low doses of these elements (particularly Cd and As) with other risk factors that appear linked to CKDu, prior to developing public health strategies to address this illness.
(Location: IWMI HQ Call no: e-copy only Record No: H048459)
(3.75 MB)
Agricultural intensification to meet the food needs of the rapidly growing population in developing countries is negatively affecting the water quality. In most of these countries such as Ethiopia, information on surface and especially groundwater quality is lacking. This limits the measure that can be taken to stop pollution. We, therefore, investigated the spatial and temporal variation of groundwater quality in the upland watershed. Tikur-Wuha watershed was selected because it is located in the Lake Tana watershed, which is seeing the first signs of eutrophication. Groundwater samples were collected from July 2014 to June 2015 from 19 shallow wells located throughout the watershed. Collected water samples were analyzed both in situ and in the laboratory to determine pH, electric conductivity (EC) and total dissolved solid (TDS), concentration of chemicals (nitrate, dissolved phosphorus, calcium, magnesium, aluminum and iron) and Escherichia coli (E. coli). We found that shallow groundwater had greater chemical concentrations and E. coli level in the monsoon rain phase than in the dry phase. Wells located down slope exhibited greater concentrations than mid- and upper-slope positions, with the exception of the nitrate concentration that was less down slope, due to denitrification in the shallow groundwater. Only E. coli level was above the WHO drinking water quality standards. Further studies on groundwater quality should be carried out to understand the extent of groundwater contamination.
(Location: IWMI HQ Call no: e-copy only Record No: H048834)
(0.86 MB) (884 KB)
Current guidelines for testing drinking water quality recommend that the sampling rate, which is the number of samples tested for fecal indicator bacteria (FIB) per year, increases as the population served by the drinking water system increases. However, in low-resource settings, prevalence of contamination tends to be higher, potentially requiring higher sampling rates and different statistical methods not addressed by current sampling recommendations. We analyzed 27,930 tests for FIB collected from 351 piped water systems in eight countries in sub-Saharan Africa to assess current sampling rates, observed contamination prevalences, and the ability of monitoring agencies to complete two common objectives of sampling programs: determine regulatory compliance and detect a change over time. Although FIB were never detected in samples from 75% of piped water systems, only 14% were sampled often enough to conclude with 90% confidence that the true contamination prevalence met an example guideline ( 5% chance of any sample positive for FIB). Similarly, after observing a ten percentage point increase in contaminated samples, 43% of PWS would still require more than a year before their monitoring agency could be confident that contamination had actually increased. We conclude that current sampling practices in these settings may provide insufficient information because they collect too few samples. We also conclude that current guidelines could be improved by specifying how to increase sampling after contamination has been detected. Our results suggest that future recommendations should explicitly consider the regulatory limit and desired confidence in results, and adapt when FIB is detected.
20 Kurki-Fox, J. J.; Doll, B. A.; Monteleone, B.; West, K.; Putnam, G.; Kelleher, L.; Krause, S.; Schneidewind, U. 2023. Microplastic distribution and characteristics across a large river basin: insights from the Neuse River in North Carolina, USA. Science of The Total Environment, 878:162940. [doi: https://doi.org/10.1016/j.scitotenv.2023.162940]
(Location: IWMI HQ Call no: e-copy only Record No: H051907)
(3.71 MB) (3.71 MB)
While microplastics (MP) have been found in aquatic ecosystems around the world, the understanding of drivers and controls of their occurrence and distribution have yet to be determined. In particular, their fate and transport in river catchments and networks are still poorly understood. We identified MP concentrations in water and streambed sediment at fifteen locations across the Neuse River Basin in North Carolina, USA. Water samples were collected with two different mesh sizes, a trawl net (>335 µm) and a 64 µm sieve used to filter bailing water samples. MPs >335 µm were found in all the water samples with concentrations ranging from 0.02 to 221 particles per m3 (p m-3) with a median of 0.44 p m-3. The highest concentrations were observed in urban streams and there was a significant correlation between streamflow and MP concentration in the most urbanized locations. Fourier Transform Infrared (FTIR) analysis indicated that for MPs >335 µm the three most common polymer types were polyethylene, polypropylene, and polystyrene. There were substantially more MP particles observed when samples were analyzed using a smaller mesh size (>64 µm), with concentrations ranging from 20 to 130 p m-3 and the most common polymer type being polyethylene terephthalate as identified by Raman spectroscopy. The ratio of MP concentrations (64 µm to 335 µm) ranged from 35 to 375, indicating the 335 µm mesh substantially underestimates MPs relative to the 64 µm mesh. MPs were detected in 14/15 sediment samples. Sediment and water column concentrations were not correlated. We estimate MP (>64 µm) loading from the Neuse River watershed to be 230 billion particles per year. The findings of this study help to better understand how MPs are spatially distributed and transported through a river basin and how MP concentrations are impacted by land cover, hydrology, and sampling method.
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