Tag Archives: Water Resources

Lake Oroville (California) on track to overflow

“After heavy winter storms, the water level stands just two feet below the new spillway gates – will it work?” click here

World’s largest solar panel farm requires 200,000 liters of good quality water each day.

“It takes as much as 2 lakh litres of good quality water to keep its 25 lakh solar modules clean each day. That water is sourced from borewells 5 km away without permission from the district authorities, the villagers allege.” click here

Water demand framework case study, China

Yahua Wang, Tingting Wan, Cecilia Tortajada. Water Demand Framework and Water Development: The Case of China Water 2018, 10 (12), 1860 https://doi.org/10.3390/w10121860

Water resources management is increasingly important for sustainable economic and social development. A coherent division of the development stages is of primary importance for selecting and implementing related water resource management strategies. Using evolving supply–demand relationships, this paper proposes a framework that considers water development stages to present a series of dynamic relationships between water demand changes and overall economic development. The framework is applied to China to advance the understanding of how demand evolves at different stages of water resources development under specific socioeconomic circumstances, and of strategic choices in general. The case of China explains how water resources management has gradually improved during distinct socioeconomic development stages. It illustrates the varieties and effectiveness of water policies made to adapt to changing demand over the course of socioeconomic development. The framework can be potentially applied to other countries or regions to identify the development stage in order to select proper water management strategies.

Majority of European Alpine glacier melt occurred prior to 1875

Sigl, M., Abram, N. J., Gabrieli, J., Jenk, T. M., Osmont, D., and Schwikowski, M.: 19th century glacier retreat in the Alps preceded the emergence of industrial black carbon deposition on high-alpine glaciers, The Cryosphere, 12, 3311-3331, https://doi.org/10.5194/tc-12-3311-2018, 2018.

“Starting around AD1860, many glaciers in the European Alps began to retreat from their maximum mid-19th century terminus positions, thereby visualizing the end of the Little Ice Age in Europe. Radiative forcing by increasing deposition of industrial black carbon to snow has been suggested as the main driver of the abrupt glacier retreats in the Alps. The basis for this hypothesis was model simulations using elemental carbon concentrations at low temporal resolution from two ice cores in the Alps.”

“Our study reveals that in AD1875, the time when rBC ice-core concentrations started to significantly increase, the majority of Alpine glaciers had already experienced more than 80% of their total 19th century length reduction, casting doubt on a leading role for soot in terminating of the Little Ice Age.”

Does watershed protection lower the cost of drinking water treatment?

Price JI, Heberling MT. The Effects of Source Water Quality on Drinking Water Treatment Costs: A Review and Synthesis of Empirical Literature. Ecological Economics 2018 Sep 3;151:195-209. doi: 10.1016/j.ecolecon.2018.04.014.

Watershed protection, and associated in situ water quality improvements, has received considerable attention as a means for mitigating health risks and avoiding expenditures at drinking water treatment plants (DWTPs). This study reviews the literature linking source water quality to DWTP expenditures. For each study, we report information on the modeling approach, data structure, definition of treatment costs and water quality, and statistical methods. We then extract elasticities indicating the percentage change in drinking water treatment costs resulting from a 1% change in water quality. Forty-six elasticities are obtained for various water quality parameters, such as turbidity, total organic carbon (TOC), nitrogen, sediment loading, and phosphorus loading. An additional 29 elasticities are obtained for land use classification (e.g., forest, agricultural, urban), which often proxy source water quality. Findings indicate relatively large ranges in the estimated elasticities of most parameters and land use classifications. However, average elasticities are smaller and ranges typically narrower for studies that incorporated control variables consistent with economic theory in their models. We discuss the implications of these findings for a DWTP’s incentive to engage in source water protection and highlight gaps in the literature.

Global models underestimate decadal water storage trends

Bridget R. Scanlon, Zizhan Zhang, Himanshu Save, Alexander Y. Sun, Hannes Müller Schmied, Ludovicus P. H. van Beek, David N. Wiese, Yoshihide Wada, Di Long, Robert C. Reedy, Laurent Longuevergne, Petra Döll, and Marc F. P. Bierkens. Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data. PNAS January 22, 2018. 201704665; https://doi.org/10.1073/pnas.1704665115.

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated.

Unverifiable Stream Water Quality Models: Believe it or Not!

Islam MMM, Iqbal MS, Leemans R, Hofstra N. Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality. International journal of hygiene and environmental health. 2017 Dec 4. pii: S1438-4639(17)30408-X. doi: 10.1016/j.ijheh.2017.11.006.

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks.