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Stavi, I.; Eldad, S.; Xu, C.; Xu, Z.; Gusarov, Y.; Haiman, M.; Argaman, E. |
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Ancient agricultural terrace walls control floods and regulate the distribution of Asphodelus ramosus geophytes in the Israeli arid Negev |
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Journal Article |
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Year |
2024 |
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Catena |
Abbreviated Journal |
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234 |
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107588 |
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Geo-archaeology, Hydrological connectivity, Hydrological modelling, Runoff harvesting, Soil and water conservation, Watershed management |
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Ancient stone terrace walls aimed at harvesting water runoff and facilitating crop production are widespread across the drylands of the Middle East and beyond. In addition to retaining the scarce water resource, the terrace walls also conserve soil and thicken its profile along ephemeral stream channels (wadis) by decreasing fluvial connectivity and mitigating erosional processes. In this study, we created hydrological models for three wadis with ancient stone terrace walls in the arid northern Negev of Israel, where the predominant geophyte species is Asphodelus ramosus L. A two-dimensional (2D) rain-on-grid (RoG) approach with a resolution of 2 m was used to simulate the rain events with return periods of 10, 20, 50, and 99 % (10-y, 5-y, 2-y, and yearly, respectively) based on the Intensity-Duration-Frequency rain curves for the region. To evaluate the effect of stone terrace walls on fluvial hydrology and geomorphology, the ground level was artificially elevated by 20 cm at the wall locations in a digital terrain model (DTM), using the built-in HEC-RAS 2D terrain modification tool. Our results showed that the terraced wadis have a high capacity to mitigate runoff loss, but a lesser capacity to delay the peak flow. Yet, for all rainstorm return periods, peak flow mitigation was positively related to the number of terrace walls along the stream channel. Field surveys in two of the studied wadis demonstrated that the A. ramosus clones were found in proximity to the stone terrace walls, presumably due to the greater soil–water content there. The results thus suggest that the terrace walls provide improved habitat conditions for these geophytes, supporting their growth and regulating their distribution along the wadi beds. |
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0341-8162 |
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THL @ christoph.kuells @ Stavi2024107588 |
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229 |
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Singh, A.; Patel, S.; Bhadani, V.; Kumar, V.; Gaurav, K. |
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Title |
AutoML-GWL: Automated machine learning model for the prediction of groundwater level |
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Journal Article |
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2024 |
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Engineering Applications of Artificial Intelligence |
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127 |
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107405 |
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AutoML, Bayesian optimisation, Groundwater, Machine learning |
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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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0952-1976 |
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THL @ christoph.kuells @ singh_automl-gwl_2024 |
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168 |
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Pisa, P.F.; Nehren, U.; Sebesvari, Z.; Rai, S.; Wong, I. |
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Chapter 17 – Nature-based solutions to reduce risks and build resilience in mountain regions |
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2024 |
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Safeguarding Mountain Social-Ecological Systems |
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115-126 |
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Nature-based solutions, mountains, climate change adaptation, disaster risk reduction, ecosystem services, SDGs |
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Nature-based solutions (NbS) are increasingly recognized as effective environmental-management measures to address societal challenges such as climate change, water and food security, and disaster risk reduction, thus contributing to human well-being and protecting biodiversity. In addition to being particularly susceptible to these challenges, mountain areas are prone to multihazard conditions, due to their steep topography and particular climatic conditions. NbS can contribute greatly to the sustainable development of mountain ecosystems. This chapter presents examples of NbS in mountain areas around the globe that demonstrate how this approach contributes to achieving sustainable development. |
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Elsevier |
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Schneiderbauer, S.; Pisa, P.F.; Shroder, J.F.; Szarzynski, J. |
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978-0-12-822095-5 |
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THL @ christoph.kuells @ Fontanellapisa2024115 |
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263 |
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Tanwer, N.; Arora, V.; Kant, K.; Singh, B.; Laura, J.S.; Khosla, B. |
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Chapter 17 – Prevalence of Uranium in groundwater of rural and urban regions of India |
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Book Chapter |
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2024 |
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Water Resources Management for Rural Development |
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213-234 |
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Distribution, Heath impacts, Remediation techniques, Sources, Uranium |
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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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Elsevier |
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Madhav, S.; Srivastav, A.L.; Izah, S.C.; Hullebusch, E. van |
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978-0-443-18778-0 |
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THL @ christoph.kuells @ madhav_chapter_2024 |
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152 |
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Marteleto, T. de P.; Abreu, A.E.S. de; Barbosa, M.B.; Yoshinaga-Pereira, S.; Bertolo, R.A.; Enzweiler, J. |
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Groundwater apparent ages and isotopic composition in Crystalline, Diabase and Tubarão aquifers contact area in Campinas, Southeastern Brazil |
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2024 |
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Journal of South American Earth Sciences |
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135 |
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104783 |
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Fractured aquifer, Groundwater mixing, Isotopes, Water management |
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This study refines the hydrogeological conceptual model of an area with three interconnected aquifers, namely the Crystalline Aquifer System (CAS – igneous and metamorphic rocks), which is in contact with the Tubarão Aquifer System (TAS – sedimentary rocks) and the Diabase Aquifer System (DAS – diabase rocks). The detailed investigation involved geophysical logging and hydraulic and hydrodynamic characterization with straddle packers in a local tubular well, in which groundwater presents high uranium concentrations. Hydrogeochemical and isotope (δ2H, δ18O, 3H, δ13C, 14C) analysis in this well and in other three neighboring wells, with lower U concentrations, showed that ancient and modern waters (3H from <0.8 to 1.12 TU, 14C from 69.43 to 78.72 pMC) mix within the aquifer. During groundwater pumping, vertical fractures in the diabase aquifer possibly induce water mixing and recharge of the deeper levels of the aquifers from shallow layers. The high [U] are related to ancient waters from a confined aquifer hosted in CAS that reaches the wells through hydraulically active fractures located deeper than 159 m depth. Groundwater apparent ages do not increase systematically with depth, revealing a complex circulation model for CAS. The results obtained from the other wells, which are all located on drainage lineaments, reveal that one extracts modern water from DAS and TAS, another one extracts modern and ancient water from DAS and CAS, and the third extracts only ancient water from CAS, confirming the complexity of the local hydrogeology. Regarding regional groundwater management, the study revealed the need to characterize the sources of groundwater in each well, in order to protect modern waters from anthropogenic contamination and to protect ancient groundwater from overexploitation, as CAS hosts groundwaters recharged thousands of years ago or more. |
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0895-9811 |
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THL @ christoph.kuells @ Depaulamarteleto2024104783 |
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221 |
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