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Hayes-Rich, E., Levy, J., Hayes-Rich, N., Lightfoot, D., & Gauthier, Y. (2023). Searching for hidden waters: The effectiveness of remote sensing in assessing the distribution and status of a traditional, earthen irrigation system (khettara) in Morocco. Journal of Archaeological Science: Reports, 51, 104175.
Abstract: This paper presents the results of a multi-year, interdisciplinary project that aimed to assess the holistic status of the khettara system in Morocco. The khettara (also known as qanat) is a traditional, earthen water management system. Historically the system was used for settlement in regions without access to reliable surface water. It is both a world and local heritage structure, found in rural and urban regions throughout 46 countries. Recent evaluations of this traditional system have advocated for its preservation and use in arid and semi-arid regions, as modern technologies (pump wells, industrial dams, drip irrigation, etc.) have proven to be unsustainable. This project evaluates remote sensing as a tool for assessing the distribution and status of the khettara in Morocco. The results of this project demonstrate that (1) the khettara system played a large role in the historic settlement of arid and semi-arid regions, and (2) the system continues to be an important part of agriculture and life in many oases across Morocco.
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Mekuria, W., & Tegegne, D. (2023). Water harvesting. In M. J. Goss, & M. Oliver (Eds.), Encyclopedia of Soils in the Environment (Second Edition) (pp. 593–607). Oxford: Academic Press.
Abstract: Water harvesting is the intentional collection and concentration of rainwater and runoff to offset irrigation demands. Secondary benefits include decreased flood and erosion risk. Water harvesting techniques include micro- and macro-catchment systems, floodwater harvesting, and rooftop and groundwater harvesting. The techniques vary with catchment type and size, and the method of water storage. Micro-catchment water harvesting, for example, requires the development of small structures and targets increased water delivery and storage to the root zone whereas macro-catchment systems collect runoff water from large areas. The sustainability of water harvesting techniques at the local level are usually constrained by several factors such as labor, construction costs, loss of productive land, and maintenance, suggesting that multiple solutions are required to sustain the benefits of water harvesting techniques.
Keywords: Climate change, Ecosystem services, Environmental benefits, Population growth, Resilient community, Resilient environment, Socio-economic benefits, Urbanizations, Water harvesting, Water quality, Water security
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Abadi, B., Sadeghfam, S., Ehsanitabar, A., & Nadiri, A. A. (2023). Investigating socio-economic and hydrological sustainability of ancient Qanat water systems in arid regions of central Iran. Groundwater for Sustainable Development, 23, 100988.
Abstract: The Qanat water systems (QWSs), the ancient water engineering systems in Iran belonging to the very distant past, have harvested groundwater from drainages to convey it toward the surface with no use of energy. The present article highlights the socio-economic aspects of the sustainability of the QWSs and gives a satisfactory explanation of why the QWSs should be restored. In doing so, we subscribe to the view that indigenous and scientific knowledge should be incorporated. The former serves to tackle the restoration of the QWSs, the latter contributes to the distribution of water into the farmlands as efficiently as possible. Measured by (a) resilience, (b) reliability, (c) vulnerability, and (d) sustainability, the GIS technique made clear the performance of the QWSs has, therefore, the worst condition observed in terms of resiliency; the best condition observed concerning the vulnerability. Moreover, the QWSs have intermediate performance in terms of reliability. Finally, the sustainability index (SI) classifies the QWSs into different bands, which provide explicit support to take priority of the selection of the QWSs for restoration. In conclusion, a theoretical framework has been drawn to keep the QWSs sustainable.
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Zhang, Y., Liu, X., Yuan, S., Song, J., Chen, W., & Dias, D. (2023). A two-dimensional experimental study of active progressive failure of deeply buried Qanat tunnels in sandy ground. Soils and Foundations, 63(3), 101323.
Abstract: As an ancient underground hydraulic engineering facility, the Qanat system has been used to draw groundwater from arid regions. A qanat is a horizontal tunnel with a slight incline that draws groundwater from a higher location and delivers it to lower agricultural land. During long-term water delivery, the qanat tunnel has experienced different degrees of aging and collapse, which may result in the significant ground settlement and even disasters. This paper developed a two-dimensional laboratory system to investigate the influence of progressive failure on the stability of deeply buried qanat tunnels. The developed system is fully instrumented with a particle image velocimetry (PIV) system and earth pressure and displacement monitoring. A special cylindrical membrane tube is designed and connected to an advanced pressure–volume controller to simulate the step-wise failure process of the tunnel. Three model tests were conducted on a dry sand considering the buried qanat tunnels at three different depths. Experimental results clearly show the progressive evolution of soil arching effect in the dry sand associated with the progressive failure of the tunnels. The failure of the Qanat ground starts from the vault and develops upwards, which is closely related to the evolution of stress contour at three consecutive stages. Ground surface settlement and volume loss corresponding to three burial depths were compared. A deeply buried qanat tunnel has a small effect on surface settlement. Earth pressure evolution on the 2D plane shows the load redistribution when the qanat collapses. The maximum arch and the initial point of the limit state correspond to a volume loss of 12.5 % and 50 %, respectively. For the collapse of the deep buried qanat tunnel, ground earth pressure evolution can be divided into a stress-increasing region, stress-decreasing region, and no redistribution region. Furthermore, a multi trap-door model considering soil expansion is proposed to describe the progressive failure behavior and its effects.
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Weerahewa, J., Timsina, J., Wickramasinghe, C., Mimasha, S., Dayananda, D., & Puspakumara, G. (2023). Ancient irrigation systems in Asia and Africa: Typologies, degradation and ecosystem services. Agricultural Systems, 205, 103580.
Abstract: CONTEXT Ancient irrigation systems (AISs) have been providing a multitude of ecosystem services to rural farming and urban communities in Asia and Africa, especially in arid and semi-arid climatic areas with low rainfall. Many AISs, however have now been degraded. A systematic analysis of AISs on their typologies, causes of degradation, and their ecosystem services is lacking. OBJECTIVE The objective of this review was to synthesize the knowledge on AISs on their typologies, status and causes of degradation, ecosystem services and functions, and identify gaps in research in Asia and Africa. METHOD A critical review of peer-reviewed journal papers, conference and workshop proceedings, book chapters, grey literature, and country reports was conducted. Qualitative and quantitative information from journal papers were used to conceptualize the typologies and analyze the status and causes of degradation, and ecosystems services and functions provided by the AISs. RESULTS AND CONCLUSION Based on the review, we classified AISs into three groups by source of irrigation water: Rainwater harvesting system (RHS) with small reservoirs, ground water based system, and floodwater based system. The RHSs, which used to receive reliable rainfall and managed by well cohesive social organizations for their maintenance and functioning in past, have now been silting due to extreme rainfall pattern and breakdown of the cohesive organizations in recent decades. In ground water based systems, indiscriminate development of deep tube wells causing siltation of channels has been a major challenge. In floodwater irrigation systems, irregular rainfall in the highlands and the breakage of irrigation structures by destructive floods were the main causes of degradation. Lack of maintenance and increased soil erosion, inadequate skilled manpower, and declining support from the government for repair and maintenance were the main causes of degradation of all AISs. The main ecosystem service provided by all AISs is water for agriculture. In tank- and pond-based systems, fish farming is also practiced. Tank irrigation systems provide various types of provisioning, regulatory, cultural and supporting services, especially in India and Sri Lanka. Ground water based systems provide water for domestic purposes and various cultural services. Floodwater based systems provide water for power generation and wildlife habitat maintenance and help in flood control. SIGNIFICANCE The knowledge generated through the review provide evidence-based information, and help aware governments, private sectors and development agencies for improved policy planning and decision making, and prioritizing the restoration, rehabilitation, and management of various AISs.
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Ollivier, C. C., Carrière, S. D., Heath, T., Olioso, A., Rabefitia, Z., Rakoto, H., et al. (2023). Ensemble precipitation estimates based on an assessment of 21 gridded precipitation datasets to improve precipitation estimations across Madagascar. Journal of Hydrology: Regional Studies, 47, 101400.
Abstract: Study region this study focuses on Madagascar. This island is characterized by a great diversity of climate, due to trade winds and the varying topography. This country is also undergoing extreme rainfall events such as droughts and cyclones. Study focus the rain gauge network of Madagascar is limited (about 30 stations). Consequently, we consider relevant satellite-based precipitation datasets to fill gaps in ground-based datasets. We assessed the reliability of 21 satellite-based and reanalysis precipitation products (P-datasets) through a direct comparison with 24 rain gauge station measurements at the monthly time step, using four statistical indicators: Kling-Gupta Efficiency (KGE), Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Bias. Based on this first analysis, we produced a merged dataset based on a weighted average of the 21 products. New hydrological insights for the region based on the KGE and the CC scores, WFDEI (WATCH Forcing Data methodology applied to ERA-Interim), CMORPH-BLD (Climate Prediction Center MORPHing satellite-gauge merged) and MSWEP (Multi-Source Weighted Ensemble Precipitation) are the most accurate for estimating rainfall at the national scale. Additionally, the results reveal a high discrepancy between bio-climatic regions. The merged dataset reveals higher performance than the other products in all situations. These results demonstrate the usefulness of a merging approach in an area with a deficit of rainfall data and a climatic and topographic diversity.
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Zwartendijk, B. W., Ghimire C. P., Ravelona M., Lahitiana J., & van Meerveld H. J. (2023). Hydrometric data and stable isotope data for streamflow and rainfall in the Marolaona catchment, Madagascar, 2015-2016. NERC EDS Environmental Information Data Centre.
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Patel, D., Pamidimukkala, P., & Chakraborty, D. (2024). Groundwater quality evaluation of Narmada district, Gujarat using principal component analysis. Groundwater for Sustainable Development, 24, 101050.
Abstract: In the present study, the ground water quality parameters were monitored during pre- and post-monsoon seasons across Narmada district, Gujarat, India. Monitoring was done in 89 drinking water samples collected by grid sampling method from the study area. Uranium and fluoride were analyzed along with associated parameters such as pH, dissolved oxygen, Cl−, NO3−, F−, SO42−, total alkalinity, total dissolved solids and hardness. In 4% samples the fluoride content was found to be above WHO permissible limits of 1.5 mg/L (2.36 mg/L in Undaimandava, 1.55 mg/L in Shira, 3.04 mg/L in Fatehpur and 1.83 mg/L in Dholivav) during pre-monsoon season (PRM) and 4.74 mg/L, 2.41 mg/L, 2.34 mg/L and 3.99 mg/L respectively in Bantawadi, Shira, Undai Mandava and Fatepur villages during post-monsoon (POM). The uranium level was within WHO limits in both POM and PRM seasons. The quality of the water was evaluated by Principal Component and Pearson Correlation statistical analysis techniques. The PRM and POM correlation study indicated a strong correlation of TDS with EC, Chloride, total alkalinity and bicarbonate and U while moderately strong correlation of TDS with fluoride were observed indicating that chloride, total alkalinity, bicarbonate, U and fluoride contributed to TDS and EC. Principal component analysis was applied for 14 variables, from which 3 factors were extracted during PRM and POM seasons. The extracted components, contributed 84.391% and 83.315%, to variation during PRM and POM seasons respectively. The study indicated that the analyzed water samples in Narmada district were safe for drinking purpose. However, Tilakwada tehsil groundwater was observed to be unsustainable for drinking, without further water treatment, but was appropriate for agricultural purposes. The study will help the residents of the district to understand the present water quality status and will also help in future management to protect the ground water of Narmada district.
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Tanwer, N., Arora, V., Kant, K., Singh, B., Laura, J. S., & Khosla, B. (2024). Chapter 17 – Prevalence of Uranium in groundwater of rural and urban regions of India. In S. Madhav, A. L. Srivastav, S. C. Izah, & E. van Hullebusch (Eds.), Water Resources Management for Rural Development (pp. 213–234). Elsevier.
Abstract: Abnormally high uranium (U) prevalence in groundwater is a neoteric subject of concern throughout the world because of its direct impact on human health and well-being. Groundwater is used as the most preferred choice for drinking because of its good quality and ease of availability in rural and urban parts of India, and also in different parts of the world. India is an agriculture-dominant country and its 50–80% irrigational requirement is met by groundwater, besides this nearly 90% of rural and 50% of urban water needs are fulfilled by groundwater. The uranium concentration in groundwater in different parts of India namely Punjab, Haryana, Rajasthan, Madhya Pradesh, Karnataka, etc. found to be varying from 0 mg/L to 1443 mg/L, and in different parts of the world, it is found up to 1400 mg/L in the countries like United States, Canada, Finland, Mongolia, Nigeria, South Korea, Pakistan, Burundi, China, Afghanistan, etc. Various natural factors such as geology, hydro-geochemistry, and prevailing conditions as well as anthropogenic factors including mining, nuclear activities, erratic use of fertilizers, and overexploitation of groundwater resources are responsible for adding uranium in groundwater. Groundwater is considered a primary source of uranium ingestion in human beings as it contributes 85% while food contributes 15%. Uranium affects living beings as a two-way sword, being a radioactive element, causing radiotoxicity, and on the other hand as a heavy metal, it causes chemotoxicity. The main target organs affected by the consumption of uranium-contaminated water are kidneys, bones, lungs, etc. It can cause renal failure, impair cell functioning and bone growth, and mutation in DNA. Although, its toxic effects, being a heavy metal, are more severe than its radiotoxicity. Various techniques are available for the efficient removal of uranium from the groundwater such as bioremediation, nanotechnology-enhanced remediation, adsorption, filtration, etc. This chapter entails a comprehensive investigation of uranium contamination in groundwater of rural and urban parts of India their probable sources, health impacts, treatment, and mitigation techniques available to manage groundwater resources.
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Singh, A., Patel, S., Bhadani, V., Kumar, V., & Gaurav, K. (2024). AutoML-GWL: Automated machine learning model for the prediction of groundwater level. Engineering Applications of Artificial Intelligence, 127, 107405.
Abstract: Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective water resource governance. However, groundwater level prediction is intricate, driven by dynamic nonlinear factors. To comprehend the dynamic interaction among these drivers, leveraging machine learning models can provide valuable insights. The drastic increase in computational capabilities has catalysed a substantial surge in the utilisation of machine learning-based solutions for effective groundwater management. The performance of these models highly depends on the selection of hyperparameters. The optimisation of hyperparameters is a complex process that often requires application-specific expertise for a skillful prediction. To mitigate the challenge posed by hyperparameter tuning’s problem-specific nature, we present an innovative approach by introducing the automated machine learning (AutoML-GWL) framework. This framework is specifically designed for precise groundwater level mapping. It seamlessly integrates the selection of best machine learning model and adeptly fine-tunes its hyperparameters by using Bayesian optimisation. We used long time series (1997-2018) data of precipitation, temperature, evaporation, soil type, relative humidity, and lag of groundwater level as input features to train the AutoML-GWL model while considering the influence of Land Use Land Cover (LULC) as a contextual factor. Among these input features, the lag of groundwater level emerged as the most relevant input feature. Once the model is trained, it performs well over the unseen data with a strong correlation of coefficient (R = 0.90), low root mean square error (RMSE = 1.22), and minimal bias = 0.23. Further, we compared the performance of the proposed AutoML-GWL with sixteen benchmark algorithms comprising baseline and novel algorithms. The AutoML-GWL outperforms all the benchmark algorithms. Furthermore, the proposed algorithm ranked first in Friedman’s statistical test, confirming its reliability. Moreover, we conducted a spatial distribution and uncertainty analysis for the proposed algorithm. The outcomes of this analysis affirmed that the AutoML-GWL can effectively manage data with spatial variations and demonstrates remarkable stability when faced with small uncertainties in the input parameters. This study holds significant promise in revolutionising groundwater management practices by establishing an automated framework for simulating groundwater levels for sustainable water resource management.
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