M. Mahmoodi; M. Honarmand; F. Naseri; S. Mohammadi
Abstract
Introduction: Runoff estimation is one of the main concerns of hydrologists and plays a key role in various engineering calculations and designs. Many factors such as climate, topography, soil properties, land cover, etc, are involved in producing surface runoff. Land use and land cover changes have ...
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Introduction: Runoff estimation is one of the main concerns of hydrologists and plays a key role in various engineering calculations and designs. Many factors such as climate, topography, soil properties, land cover, etc, are involved in producing surface runoff. Land use and land cover changes have a direct impact on the hydrological cycle in the ecosystem. The most common model of surface runoff estimation is the curve number model developed by the US Soil Conservation Service (SCS-CN). Accurate estimation of its important parameters increases its precision and performance. Land use is one of the most important parameters of this model.Remote sensing (RS) and geographic information system (GIS) technologies are used in order to increase its speed and accuracy of estimation. One of the problems that have occurred in the Kashaf-Rood Basin is the extensive land use changes that may cause changes in peak discharge and surface runoff volume. In this study, due to the great importance and impact of land cover change on increasing flood risk, the effects of land use change over 28 years (from 1987 to 2015) on flood hydrograph characteristics were investigated.
Materials and Methods: The Kashaf-Rood basin is a part of the Ghara-Ghum basin. The total area of the basin is 16779 square kilometers with the highest and lowest elevation of 3235 and 378 meters above sea level, respectively . The length of the Kashaf-Rood River from the highest point to the outlet of the basin is about 374 km and its average and gross river slope are 0.0028 and 0.0043 m/m, respectively. The digital elevation model was used to calculate the topographical properties, hydrological properties and geometrical corrections required on satellite images. In this research, the data of the Global Digital Elevation Model (ASTER) with a spatial accuracy of 30 m was used. Also, the soil hydrologic group map prepared in Ghara-Ghum water resources balance studies was used. Since no land use change occurs in the short term and can be detected at long intervals, a 28-year interval was chosen for satellite imagery. In general, five images of Landsat satellite are needed for full coverage of the Kashaf-Rood Basin. For the oldest data, Landsat 5 images and for the latest data, Landsat 8 images were used. ERDAS IMAGINE 2014 software was used to digitally process satellite images. The images were classified in three methods: The Minimum distance, Mahalanobis distance and the Maximum Likelihood. In order to select the appropriate method, after applying different classification algorithms for the image of 2015, the accuracy of their classification was evaluated and, the image of 1987 was also classified based on the selected method. By combining soil hydrological group and land use map derived from Landsat satellite imagery using ArcGIS 10.3 software, the curve number maps for 1987 and 2015 were prepared. In the present study, the US soil conservation service standard curve number method (SCS-CN) was used to calculate the amount of rainfall and losses in the HEC-HMS model. For the calibration of the HEC-HMS model, four flood events at the bridge of Khatun Kashaf-Rood hydrometric station with relatively concomitant precipitation were selected. Three flood events were used for calibration and one flood event for validation.
Results and Discussion: The images were classified into three methods: The Minimum distance, Mahalanobis distance, and the Maximum Likelihood. Comparing the results of these three methods showed that their overall accuracy in evaluating and identifying land use was 78.5, 83.7 and 87.3, respectively. Thus, the maximum likelihood algorithm was used to classify the images and the image of the year 1987 was classified with this method. Ten land use classes were identified in the study area. The results showed that during the 28 years of study, the area of rocky lands and rangelands did not change. The highest percentage of change was due to water zones, poor rangelands and residential lands, which increased by 189, 143 and 50 percent, respectively. The highest amount of increase in the area occurred in the poor rangelands, which 1514 km2, and the highest decrease occurring in moderate rangelands which is 1278 km2. By combining soil hydrological group maps and land use maps in ArcGIS software and using standard tables, the curve number maps for 1987 and 2015 were prepared. The weighted average of the curve number in the mean moisture conditions for 1987 and 2015 was 77.5 and 78.4 units, respectively. After performing the calibration and validation steps, the HEC-HMS hydrological model was used to investigate the impact of land-use change on the flood hydrograph of the Kashaf-Rood River between 1987 and 2015. According to the results, in all four events which were studied, land-use changes have increased the peak of discharge and the flood volume over the 28 years of study. On average, the peak flood discharge in 2015 was 15.2% higher than the peak flood discharge in 1987, and similarly, the flood volume increased by 13.7% during the study period.
Conclusion: In conclusion, it can be derived that in recent decades, land-use changes which were caused by human interference, affected the flood characteristics and increased the risk of flooding in the Kashaf-Rood river. Therefore, land use must be managed and prevented further destruction of natural resources to prevent flooding in the area.
Ali Morshedi; Seyed Hassan Tabatabaei; Mahdi Naderi
Abstract
Introduction: Evapotranspiration (ET) is an important component of the hydrological cycle, energy equations at the surface and water balance. ET estimation is needed in various fields of science, such as hydrology, agriculture, forestry and pasture, and water resources management. Conventional methods ...
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Introduction: Evapotranspiration (ET) is an important component of the hydrological cycle, energy equations at the surface and water balance. ET estimation is needed in various fields of science, such as hydrology, agriculture, forestry and pasture, and water resources management. Conventional methods used to estimate evapotranspiration from point measurements. Remote sensing models have the capability to estimate ET using surface albedo, surface temperature and vegetation indices in larger scales. Surface Energy Balance Algorithm for Land (SEBAL) estimate ET at the moment of satellite path as a residual of energy balance equation for each pixel. In this study Hargreaves-Samani (HS) and SEBAL models ET compared to an alfalfa lysimeter data’s, located in Shahrekord plain within the Karun basin. Satellite imageries were based on Landsat 7 ETM+ sensor data’s in seven satellite passes for path 164 and row 38 in the World Reference System, similar to lysimeter sampling data period, from April to October 2011. SEBAL uses the energy balance equation to estimate evapotranspiration. Equation No. 1 shows the energy balance equation for an evaporative surface:
λET=Rn–G–H [1]
In this equation Rn, H, G and λET represent the net radiation flux input to the surface (W/m2), Sensible heat flux (W/m2), soil heat flux (W/m2), and latent heat of vaporization (W/m2), respectively. In this equation the vertical flux considered and the horizontal fluxes of energy are neglected. The above equation must be used for large surfaces and uniformly full cover plant area. SEBAL is provided for estimating ET, using the minimum data measured by ground equipment. This model is applied and tested in more than 30 countries with an accuracy of about 85% at field scale, and 95 percent in the daily and seasonal scales. In Borkhar watershed (East of Isfahan, IRAN) ASTER and MODIS satellite imageries were used for SEBAL to compare Penman-Monteith model. Results showed that estimated ET of SEBAL were about 20% less than sugar beet ET and about 15% more for maize ET by Penman-Monteith. He concluded the differences may be due to the limited number of satellite imageries which extrapolated ET through the entire growth period and the data obtained from the weather station far from 24 km in the studied area. In another study at Zayanderud Basin, the different irrigation networks were examined using Landsat 7 imageries to increase the spatial resolution of NOAA satellite to determine the energy balance components and actual evapotranspiration. In this study, data from a lysimeter to a depth of 2.5 m and a diameter of 3 meters planted with alfalfa in the Chahar-Takhteh agricultural research station (Agricultural and natural resources research center of Shahrekord, IRAN) was used. The lysimeter (LYS_REF) located in the in the middle of 25 × 40 m (1000 square meter) alfalfa cultivated farm, surrounded by other planted area. The lysimeter used to measure the reference evapotranspiration (ETr) and around alfalfa was used as cold pixels.
Materials and Methods: This study was conducted to evaluate SEBAL and Hargreaves-Samani estimated ET models against evapotranspiration measured by lysimeter within the Shahrekord plain. Meteorological data required for a period of 185 days (according to the lysimeter data period) includes minimum and maximum relative humidity (RHmax and RHmin), maximum and minimum air temperature (Tmax and Tmin), wind speed at two meters (U2), precipitation, evaporation rate, sunshine hours, air pressure and dew point temperature obtained from a weather station nearby lysimeter. In order to assess reference evapotranspiration (ETr) models, statistical indices such as the coefficient of determination (R2), mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE) and index of agreement (d) were used.
Results and Discussion: The results showed that RMSE, MAE and MBE for SEBAL model over the lysimeter data were 1.782, 1.275 and -0.272 mm/day and 0.700 for the d index, respectively. Similar indices for the Hargreaves-Samani model were 1.003, 0.580 and 0.290 mm/day and 0.917 for the d index. For HS model results show that RMSE, MAE and MBE values were 0.813, 0.477 and 0.206 mm/day, and 0.930 for the index of d, during the entire growing period (185 days).
Conclusion: However, results showed that the efficiency and reliability of the SEBAL model by processing satellite visible, near infrared and thermal infrared bands. The need for irrigation water requirements and ET estimation are noteworthy, during the growth of various plants, which vary and thus the complete time series of satellite imageries is required to estimate the total and annual evapotranspiration.
