Remotely sensed data can reinforce the abilities of water resources researchers and decision-makers to monitor water quality more effectively. In the past few decades, remote sensing techniques have been widely used to measure qualitative water quality parameters. However, the use of moderate resolution sensors may not meet the requirements for monitoring small water bodies. Water quality in a small dam was assessed using high-resolution satellite data from RapidEye and in situ measurements collected a few days apart. The satellite carries a five-band multispectral optical imager with a ground sampling distance of 5 m at its nadir and a swath width of 80 km. Several different algorithms were evaluated using Pearson correlation coefficients for electrical conductivity (EC), total dissolved soils (TDS), water transparency, water turbidity, depth, suspended particular matter (SPM), and chlorophyll-a. The results indicate strong correlation between the investigated parameters and RapidEye reflectance, especially in the red and red-edge portion with highest correlation between red-edge band and water turbidity (r2 = 0.92). Two of the investigated indices showed good correlation in almost all of the water quality parameters with correlation higher than 0.80. The findings of this study emphasize the use of both high-resolution remote sensing imagery and red-edge portion of the electromagnetic spectrum for monitoring several water quality parameters in small water areas.
Watershed models that combine hydrology and water quality are being widely used in integrated watershed management for the determination of best water management practices. In this study, the hydrology of the Lower Porsuk Stream Watershed in Turkey has been modelled with the Soil and Water Assessment Tool to determine optimal water management strategies. The calibration and the validation process have been accomplished using data from two monitoring stations. The model has been run for the 1978–2009 period, and while the 1998–2004 period has been used for calibration, the validation has spanned the whole period. The SWATCup calibration and uncertainty program has been used for this purpose. No significant differences have been detected among different iteration numbers in the calibration period. The monthly Nash–Sutcliffe and R2 performance indicators for the upstream Esenkara station have been 0.74 and 0.88, respectively, for the calibration period, and 0.87 and 0.87, respectively, for the validation period. The Kiranharmani station, which is located close to the watershed outlet, has shown values of 0.59 and 0.72, respectively, for the calibration period, and 0.44 and 0.56, respectively, for the validation period. There are uncertainties in the abstracted irrigation and groundwater quantities that have reflected in the results in the Kiranharmani station, which is more affected as it lies downstream of the irrigation areas. The effects of different irrigation practices on the flow regime have been also investigated. A scenario has been implemented in which drip irrigation wholly replaces conventional furrow and sprinkler irrigation. The scenario has shown increases in stream flows by 87% for the whole year. The adoption of more efficient irrigation practices thus results in reducing the water stress induced by irrigation demands. With this study, a modelling framework has been founded to aid water management applications in the Lower Porsuk Stream Watershed by generating scenarios for best management practices. Copyright © 2012 John Wiley & Sons, Ltd.
This study deals with the effects of the expected climate change on the hydrology of watersheds and on water resources. HSPF (Hydrological Simulation Program-Fortran) has been used to model streamflow and reservoir volume as realizations of watershed response. Climate change scenarios have been prepared based on trends expected in western Turkey in the first half of the twenty-first century and a hypothetical watershed with different land uses has been simulated. Changes in streamflow due to landuse, soil type and climate change have been examined using flood frequency and low flow analysis. The simulations have revealed quantitatively the difference among the responses of watersheds with no vegetative cover and with forests or pasture to trends in temperature and precipitation. It has also been found that monthly variations are very important in predicting the future response of watersheds. Significant differences have been observed in streamflows and reservoir volumes on a monthly basis between scenarios, soil types and land uses. Though the effects of temperature and precipitation act to counterbalance their effects on a long-term scale, on a monthly basis they can act to reinforce their effects and create drought periods and floods.
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