ABSTRACT
In the water-scarce basin, the allocation of environmental flows needs to achieve the equilibrium between ecological protection and economic development. One of the challenges is the lack of quantitative analysis of the value of water in the economy and ecosystem, which could not effectively support the decision-making. This paper proposed a new multi-criteria decision-making approach that considers the value trade-offs between the environmental flows and the economic water use of rivers. The value of environmental flows was assessed using the modified equivalent factor method combined with the hydraulic method, which considers the influences of the hydraulic characteristics of rivers on value assessment. The value of the economic water use was estimated using the modified Cobb-Douglas production function. The ideal point method was applied to obtain the optimal solution of the multi-criteria decision with the objective of maximum values of the economic water use and maximum values of environmental flows (or the value of multiple recommended environmental flows). This new method was applied to determine the optimal environmental flows in the Fen River, the second-largest tributary of the Yellow River of China. The results indicated that the reasonable environmental flows were 51.1 % or 40.4 % (considering the water shortage for development) of the natural runoff of the Fen River. This work could provide a valuable reference for determining the water allocation of environmental flows in the water shortage area of China.
ABSTRACT
Cold regions are particularly vulnerable to climate change. Thus, evaluating the response of water quality evolution to climate change in cold regions is vital for formulating adaptive countermeasures for pollution control under changing climatic conditions. Taking the Songhua River Basin (SRB) in Northeast China as the target area, we designed a water-heat-nitrogen coupled model based on the principle of water and energy transfer and nitrogen cycle processes model (WEP-N) in cold regions. The impact of climate change on pollution load and water quality was analyzed during the freezing, thawing, and non-freeze-thaw periods by taking the sudden change point (1998) of precipitation and runoff evolution in the SRB as the cut-off. The ammonia nitrogen load at Jiamusi station, the outlet control station in the SRB, was decreased by 1502.9 t in the change period (1999-2018) over the base period (1956-1998), with a - 9.2% decrease due to climate change. Compared to the ammonia nitrogen load during the base period, the ammonia nitrogen load decreased by - 171.3, - 506.9, and - 824.8 t during the freezing, thawing, and non-freeze-thaw periods, respectively, while the coefficient of variation showed an increasing trend during three periods, especially during the freezing and thawing periods. However, the water quality changes differed among periods owing to varying runoff during the year. Meanwhile, increasing runoff and decreasing ammonia nitrogen load improved water quality at Jiamusi station during the freezing period. During the thawing and non-freeze-thaw period, the water quality deteriorated due to the decrease in runoff more than the decrease in ammonia nitrogen load. Hence, the impact of climate change on water quality during thawing and non-freeze-thaw periods should be monitored to potentially offset the human influence on pollution control. The difference in the rate of change of the proportion of Class IV water between the two models with or without the soil freeze-thaw mechanism was 15.9%. The result shows that the application of a model that does not consider the freeze-thaw mechanism might slightly exaggerate the impact of climate change on water quality.
Subject(s)
Hot Temperature , Water Quality , Humans , Nitrogen/analysis , Climate Change , Ammonia , FreezingABSTRACT
The nitrogen cycle in cold regions during the freeze-thaw period is complex. Although previous studies have investigated the phenomenon of nitrogen transport and transformation, the underlying mechanisms are vague. Existing models have limitations in terms of loose coupling or weak physical mechanisms. Therefore, a new distributed nonpoint source pollution model, the water and energy transfer processes and nitrogen cycle processes model in cold regions, was developed in this study, with closely coupled water, heat, and nitrogen processes at the watershed scale. The model considered the driving effects of pressure, gravity, solute, and temperature potentials on water and nitrogen movement in soil and the transformation relationship among nitrogen forms. Physical evaluation and simulations were conducted for the Heidingzi River Watershed during two freeze-thaw periods: 2017-2018 and 2018-2019. The soil temperature absolute error was < 0.82 â. The relative errors in stratified liquid water, soil nitrogen content, river flow rate, and river nitrogen concentration were mostly < 10%. Nitrogen transport with water had an obvious "upward agglomeration effect" during the freezing period and a "concentrated release effect" during the thawing period, which was attributed to changes in soil water potential as the freezing front moved down. Disregarding the effects of solute potential and temperature potential will result in an underestimate of the outflow of pollutants during the thawing period. The model can be applied to reveal water quality deterioration in cold regions during thawing.
Subject(s)
Nitrogen , Non-Point Source Pollution , Freezing , Nitrogen/analysis , Hot Temperature , SoilABSTRACT
Climate change and anthropogenic activity are the primary drivers of water cycle changes. Hydrological droughts are caused by a shortage of surface and/or groundwater resources caused by climate change and/or anthropogenic activity. Existing hydrological models have primarily focused on simulating natural water cycle processes, while limited research has investigated the influence of anthropogenic activities on water cycle processes. This study proposes a novel framework that integrates a distributed hydrological model and an attribution analysis method to assess the impacts of climate change and anthropogenic activities on hydrological drought The distributed dualistic water cycle model was applied to the Fuhe River Basin (FRB), and it generated a Nash-Sutcliffe efficiency coefficient > 0.85 with a relative error of <5 %. Excluding the year with extreme drought conditions, our analysis revealed that climate change negatively impacted the average drought duration (-105.5 %) and intensity (-23.6 %) because of increasing precipitation. However, anthropogenic activities continued to contribute positively to the drought, accounting for 5.5 % and 123.6 % of the average drought duration and intensity, respectively, because of increased water consumption. When accounting for extreme drought years, our results suggested that climate change has contributed negatively to the average duration of drought (-113.2 %) but positively to its intensity (7.8 %). Further, we found that anthropogenic activities contributed positively to both the average drought duration and intensity (13.2 % and 92.2 %, respectively). While climate change can potentially mitigate hydrological drought in the FRB by boosting precipitation levels, its overall effect may exacerbate drought through the amplification of extreme climate events resulting from global climate change. Therefore, greater attention should be paid to the effects of extreme drought.
ABSTRACT
This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.