Abstract:The ongoing and proposed construction of large-scale hydropower dams in the Mekong river basin is a subject of intense debate and growing international concern due to the unprecedented and potentially irreversible impacts these dams are likely to have on the hydrological, agricultural, and ecological systems across the basin. Studies have shown that some of the dams built in the tributaries and the main stem of the upper Mekong have already caused basin-wide impacts by altering the magnitude and seasonality of flows, blocking sediment transport, affecting fisheries and livelihoods of downstream inhabitants, and changing the flood pulse to the Tonle Sap Lake. There are hundreds of additional dams planned for the near future that would result in further changes, potentially causing permanent damage to the highly productive agricultural systems and fisheries, as well as the riverine and floodplain ecosystems. Several studies have examined the potential impacts of existing and planned dams but the integrated effects of the dams when combined with the adverse hydrologic consequences of climate change remain largely unknown. Here, we provide a detailed review of the existing literature on the changes in climate, land use, and dam construction and the resulting impacts on hydrological, agricultural, and ecological systems across the Mekong. The review provides a basis to better understand the effects of climate change and accelerating human water management activities on the coupled hydrological-agricultural-ecological systems, and identifies existing challenges to study the region's Water, Energy, and Food (WEF) nexus with emphasis on the influence of future dams and projected climate change. In the last section, we synthesize the results and highlight the urgent need to develop integrated models to holistically study the coupled natural-human systems across the basin that account for the impacts of climate change and water infrastructure development. This review provides a framework for future research in the Mekong, including studies that integrate hydrological, agricultural, and ecological modeling systems.
Removal of streamside vegetation changes the energy balance of a stream, and hence its temperature. A common approach to mitigating the effects of logging on stream temperature is to require establishment of buffer zones along stream corridors. A simple energy balance model is described for prediction of stream temperature in forested headwater watersheds that allows evaluation of the performance of such measures. The model is designed for application to “worst case” or maximum annual stream temperature, under low flow conditions with maximum annual solar radiation and air temperature. Low flows are estimated via a regional regression equation with independent variables readily accessible from GIS databases. Testing of the energy balance model was performed using field data for mostly forested basins on both the west and east slopes of the Cascade Mountains, and was then evaluated using the regional equations for low flow and observed maximum reach temperatures in three different east slope Cascades catchments. A series of sensitivity analyses showed that increasing the buffer width beyond 30 meters did not significantly decrease stream temperatures, and that other vegetation parameters such as leaf area index, average tree height, and to a lesser extent streamside vegetation buffer width, more strongly affected maximum stream temperatures.
This paper examines the role of soil moisture in quantifying drought through the development of a drought index using observed and modeled soil moisture. In Nebraska, rainfall is received primarily during the crop-growing season and the supply of moisture from the Gulf of Mexico determines if the impending crop year is either normal or anomalous and any deficit of rain leads to a lack of soil moisture storage. Using observed soil moisture from the Automated Weather Data Network (AWDN), the actual available water content for plants is calculated as the difference between observed or modeled soil moisture and wilting point, which is subsequently normalized with the site-specific, soil property-based, idealistic available water for plants that is calculated as the difference between field capacity and wilting point to derive the soil moisture index (SMI). This index is categorized into five classes from no drought to extreme drought to quantitatively assess drought in both space and time. Additionally, with the aid of an in-house hydrology model, soil moisture was simulated in order to compute model-based SMI and to compare the drought duration and severity for various sites. The results suggest that the soil moisture influence, a positive feedback process reported in many earlier studies, is unquestionably a quantitative indicator of drought. Also, the severity and duration of drought across Nebraska has a clear gradient from west to east, with the Panhandle region experiencing severe to extreme drought in the deeper soil layers for longer periods (Ͼ200 days), than the central and southwestern regions (125-150 days) or the eastern regions about 100 days or less. The anomalous rainfall years can eliminate the distinction among these regions with regard to their drought extent, severity, and persistence, thus making drought a more ubiquitous phenomenon, but the recovery from drought can be subject to similar gradations. The spatial SMI maps presented in this paper can be used with the Drought Monitor maps to assess the local drought conditions more effectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.