Journal of Contemporary Water Research & Education最新文献

All 54 km of the West Fork of the White River (WFWR) were on Arkansas's 303(d) list of impaired waterbodies for turbidity, total dissolved solids (TDS), and sulfate for many years. This study identifies which river segments fail to meet applicable water quality standards (WQS) and investigates possible anthropogenic or natural sources of pollutants. We also evaluated a larger dataset of 119 sites in the Boston Mountains and Ozark Highlands ecoregions, compiled from the Arkansas Department of Environmental Quality online database. In the WFWR, water samples were collected once or twice a month at nine sites from June 2014 through June 2018. Median values for turbidity, TDS, sulfate, and chloride ranged from 1.8 to 10.8 NTU, 40.8 to 151.3 mg/L, 3.5 to 27.9 mg/L, and 3.2 to 5.5 mg/L, respectively, and generally increased from upstream to downstream (p < 0.05). Violations of the water quality standard for the parameters of interest varied by site, but generally occurred in the downstream portion of the WFWR, where land use, riparian soils, and underlying geology change. In the larger dataset, turbidity, TDS, sulfate, and chloride concentrations were all significantly greater in the Ozark Highlands than the Boston Mountains ecoregion (p < 0.05). Anthropogenic activities influence dissolved ion concentrations across these study sites, while geology and riparian soils may be important factors for differences in sulfate and turbidity.

Analysis of historic and contemporary high-resolution imagery can help to fill knowledge gaps in land cover and management history in locations where documentation is non-existent or records are difficult to access. Historic imagery dating back to the 1960s can be used to structure quantitative investigation and mapping of land use and land cover change across space and time to enhance earth science, policy, and social science research. Imagery can further inform municipal planning and implementation in areas of natural resource allocation, infrastructure, and hazard mitigation. For management and public education, historic imagery can help people to understand environmental processes and the impacts of human activity in the local environment. Here we emphasize the value of high-resolution historic satellite imagery from the Corona and Keyhole satellite programs to inform environmental research, public education, and environmental management. Within the Region of Arequipa in southern Peru we highlight examples of urban development, agricultural expansion, river channelization, and glacial retreat via comparison of historic and modern satellite imagery. By incorporating these types of historic imagery data in formats accessible to non-professionals, public engagement as well as research into human-environmental investigations will be greatly enhanced.

With growing developments in the technology of cloud storage and the Internet of Things, smart systems have become the latest trend in major agricultural regions of the world. The Arequipa and Caylloma provinces of Peru are highly productive agricultural areas that could benefit from these technologies. This region has low precipitation, generally less than 100 mm per year. Electricity is not available in most of the agricultural fields, limiting the types of irrigation methods and technologies that can be supported. Currently, 20 ponds supplied by water runoff from the Andean glaciers are used for irrigating approximately 545 hectares of land in the Majes district (Caylloma province). In order to develop optimal techniques for water irrigation in Arequipa and improve the infrastructure, there is a need for development of a smart water irrigation system applicable to the existing conditions in the region. The current study proposes a pilot smart water irrigation framework comprised of a drip irrigation module, wireless communication module, and a sensor network for intelligently regulating water flow from the cloud. In this study, a TEROS 12 soil moisture sensor is connected to a Digi XBee wireless module for collecting measurements of volumetric water content, temperature, and electrical conductivity, which are sent through a secure IP gateway to the cloud. A user-friendly web interface is available for end-users to access and analyze real-time data. The proposed framework is easily implementable, low-cost, and is predicted to conserve water through optimization of irrigation cycles based on a set moisture threshold.

In a globalized world, universities are forming partnerships to solve today's water-related challenges, such as increasing water scarcity and diminished water quality. Over the past 20 years, international university-led water research partnerships have been growing in number, including between the U.S. and countries in the Global South. While there are several examples of guidelines and best practices for executing collaborations, none focus on this type of partnership. Additionally, many international collaborations are formed between universities that have little previous experience in developing these types of partnerships. Often, critiques of partnerships happen after initiation and point to structural barriers and best practices for future collaborations, but few offer practical guidance on overcoming obstacles early on, amid an imperfect partnership. In this paper, we created a flexible collaboration framework which can be used as an evaluative tool. To model this, we conducted an internal evaluation of the Sustainable Water Management team of the Arequipa Nexus Institute, a collaboration designed to build research capacity at the Universidad Nacional de San Agustín to address local issues related to agriculture, natural resource management, and environmental change. Results highlighted project strengths and weaknesses and offered strategies to address challenges that many collaborations face. This strategy identification can serve as a guideline for improving the implementation of new or existing international university-led water research partnerships and help partners as they confront challenges at every stage of the partnership. The evaluation shows the effectiveness of using a collaboration framework as an assessment tool for international university-led water research partnerships.

Coproduction is a process that involves scientists and citizens engaging throughout the production of knowledge, decisions, and/or policies. This approach has been widely applied in an international context for addressing global environmental issues. It is customary for scientists to travel to rural communities, where both scientists and local knowledge holders work together and jointly design solutions to pressing problems. Such collaboration, however, often involves high costs for both residents and scientists, which can reduce project effectiveness. This study examines the challenges associated with coproduction in the context of changing rural livelihoods in beneficiary communities. We specifically conduct a self-analysis of the coproduction process led by our own university team, where scientists designed tools for water and crop management together with community members in Peru's Caylloma province. We collected qualitative data on the coproduction challenges in five local districts in Caylloma, using focus groups and semi-structured interviews. Our results indicate that changing socioeconomic conditions in rural communities undermined the long-term sustainability and effectiveness of the coproduction efforts and deliverables. These included increased migration, market integration, and reliance on regional institutions for water and crop management.

Hydrometeorological monitoring of weather, streamflow, and water quality is essential for understanding available water resources, protecting populations from hazard, and identifying changes in environmental conditions over time. To meet such competing goals, monitoring networks require representative parameters, uniform sampling protocols, and stable locations, selected to reliably measure the phenomenon of interest. However, budgets are always limited, and immediate operational needs and short-term decisions often influence monitoring decisions. Here, the hydrometeorological monitoring systems in Arequipa, Peru, are examined with respect to established criteria for their ability to support these competing goals. The Arequipa Department in Peru has a well-established, stable, weather monitoring program, although reliance on manual observers results in variable data quality. The lack of observations in high altitude areas limits estimation of water availability, and high temporal resolution, automatic stations are needed to improve flash flood warnings. The streamflow monitoring system is designed to quantify water transfers throughout this heavily managed system. Twenty-one discharge monitoring stations were identified to serve as Historic Hydrologic Reference Stations, but many were only operational in the 1960s and 1970s and cannot be used to evaluate environmental trends. Twelve stations are identified that should be maintained for establishment of a future reference network. State sponsored water quality monitoring in the Department is fairly new, and a stratified sampling method has been used to maximize sample locations. Uniform sampling in fewer locations along intermediate sized tributaries, at least two times per year, would improve the reliability of the system and allow better detection of change over time.