Yaser Ostovari; shoja ghorbani; Hosseinali Bahrami; Mahdi Naderi; mozhgan abasi
Abstract
Introduction: Soil erodibility (K factor) is generally considered as soil sensitivity to erosion and is highly affected by different climatic, physical, hydrological, chemical, mineralogical and biological properties. This factor can be directly determined as the mean rate of soil loss from standard ...
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Introduction: Soil erodibility (K factor) is generally considered as soil sensitivity to erosion and is highly affected by different climatic, physical, hydrological, chemical, mineralogical and biological properties. This factor can be directly determined as the mean rate of soil loss from standard plots divided by erosivity factor. Since measuring the erodibility factor in the field especially watershed scale is time-consuming and costly, this factor is commonly estimated by pedotransfer functions (PTFs) using readily available soil properties. Wischmeier and Smith (1978) developed an equation using multiple linear regressions (MLR) to estimate erodibility factor of the USA using some readily available soil properties. This equation has been used to estimate K based on soil properties in many studies. As using PTFs in large sales is limited due to cost and time of collecting samples, recently soil spectroscopy technique has been widely used to predict certain soil properties using Point SpectroTransfer Functions (PSTFs). PSTFs use the correlation between soil spectra in Vis-NIR (350-2500 nm) and certain soil properties. The objective of this study was to develop PSTFs and PTFs for soil erodibility factor prediction in the Simakan watershed Fars, Iran.
Materials and Methods: The Semikan watershed, which mainly has calcareous soil with more than 40% lime (total carbonates), is located in the central of Fars province, between 30°06'-30°18'N and 53°05'-53°18'E (WGS′ 1984, zone 39°N) with an area of about 350 km2. For this study, 40 standard plots, which are 22.1×1.83 m with a uniform ploughed slope of 9% in the upslope/downslope direction, were installed in the slopes of 8-10% and the deposit of each plot was collected after rainfall. From each plot three samples were sampled and some physicochemical properties including soil texture, organic matter, water aggregate stability, soil permeability, pH, EC were analyzed Spectra of the air-dried and sieved soil samples were recorded in the Vis-NIR-SWIR (350 to 2500 nm) range at 1.4- to 2-nm sampling intervals in a standard and controlled dark laboratory environment using a portable spectroradiometer apparatus (FieldSpec 3, Analytical Spectral Device, ASD Inc.). Some bands which had the highest correlation with K factor were chosen as input parameter for developing PSTFs. A stepwise multiple linear regression method was used for developing PTFs and SPTFs. R2, RMSE and ME were used for comparing PTFs and SPTFs.
Results and Discussion: The K values varied from 0.005 to 0.023 t h MJ−1 mm−1 with an average standard deviation of 0.014 and of 0.003 t h MJ−1 mm−1, respectively. The K estimated by Wischmeier and Smith (1978) equation varied from 0.015 to 0.045 t h MJ−1 mm−1 with an average of 0.030 t h MJ−1 mm−1. There was a significant difference (p
sara kalbali; Shoja Ghorbani-Dashtaki; Mahdi Naderi; Salman Mirzaee
Abstract
Introduction: Rock fragments on soil surfaces can also have several contrasting effects on the hydraulics of overland flow and soil erosion processes. Many investigators have found that a cover of rock fragments on a soil surface can decrease its erosion potential compared to bare soil surface (1, 12 ...
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Introduction: Rock fragments on soil surfaces can also have several contrasting effects on the hydraulics of overland flow and soil erosion processes. Many investigators have found that a cover of rock fragments on a soil surface can decrease its erosion potential compared to bare soil surface (1, 12 and 18). This has mainly been attributed to the protection of the soil surface by rock fragments against the beating action of rain. This leads to a decrease in the intensity of surface sealing, an increase in the infiltration rate, a decrease in the runoff volume and rate, and, hence, a decrease in sediment generation and production for soils covered by rock fragments. Parameters that have been reported to be important for explaining the degree of runoff or soil loss from soils containing rock fragments include the position and size (15), geometry (18), and percentage cover (11 and 12) of rock fragments and the structure of fine earth (16). Surface rock fragment cover is a more important factor for hydroulic properties of surface flows such as flow depth, flow velocity, Manning’s roughness coefficient (n parameter) and flow shear stress and geometrics properties of formed rill such as time, location, number, length, width and depth of rill. Surface rock fragment cover is directly affected soil erosion processes in dry area specially in areas that plant can not grow because of sever dryness and salinity. Also, Surface rock fragment prevent the contact of rain drops to aggregates, decreasing physical degradation by decreasing flow velocity. The objective of this study was to investigate the effect of different surface rock fragment cover on hydraulic properties of surface flows and geometrics properties of formed rill.
Materials and Methods: For this purpose, 36 field plots of 20 meter length and 0.5 meter width with 3% slope were established in research field of agricultural faculty, Shahrekord University. Before each erosion event, topsoil was tilled and smoothed with hand tools to remove soil irregularities and soil sealing, update aggregates which come from deeper soil. Then, for beginning the experiment, surface rock fragment cover is scattered randomly on plot surface. Experiment equipment such as collecting the runoff systems installed at the end of plots. In each experiment after setting the surface flow, surface runoff inter to soil surface and testing continued for 60 minutes after starting runoff. Flow velocity was measured using a dye-tracing technique (potassium permanganate) and depth, width and length of rill were measured using a ruler. Treatments were including four level rock fragment cover (0, 10, 20 and 30%) and three rate runoff (2.5, 5 and 7.5 L min-1) with three replications that experiments were done in a factorial with randomized complete block design. Surface runoff samples were oven-dried and weighed to determine sediment loads. Sediment concentration was determined as the ratio of dry sediment mass to runoff volume, while the erosion rate was calculated as the sediment yield per unit area per period of time.
Results and Discussion: The results of this study showed that surface rock fragment cover plays an important role in water distribution. Based on the results, the positive effects of rock fragment cover on Manning’s n and the negative effect on flow velocity. Increasing surface rock fragment cover increased hydroulic properties such as flow depth, Manning’s n and flow shear stress significantly (p
Farzin Parchami-Araghi; seyed majid mirlatifi; Shoja Ghorbani Dashtaki; Majid Vazifehdoust; Adnan Sadeghi-Lari
Abstract
Introduction: In order to provide more realistic representation of processes governing the water and energy balances as well as water quality and plant physiological processes, weather data are needed at finer timescales than currently are available at most regions. In this study, a physically based ...
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Introduction: In order to provide more realistic representation of processes governing the water and energy balances as well as water quality and plant physiological processes, weather data are needed at finer timescales than currently are available at most regions. In this study, a physically based framework was developed to disaggregate daily weather data needed for estimation of subdaily reference evapotranspiration, including air temperature, wind speed, dew point, actual vapour pressure, relative humidity, and solar radiation. In this paper, the results of performance comparison of the utilized disaggregation approaches are presented.
Materials and Methods: In developed framework, missing daily weather data are filled by implementation of a search-optimization algorithm. Meanwhile, disaggregation models can be calibrated using Unified Particle Swarm Optimization (UPSO) algorithm. Daily and subdaily solar radiation is estimated, using a general physically based model proposed by Yang et al. (YNG model). Long-term daily and three-hourly weather data obtained from Abadan (59 years) and Ahvaz (50 years) synoptic weather stations were used to evaluate the performance of the developed framework. In order to evaluate the accuracy of the different disaggregation models, the mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and Pearson correlation coefficient (r), and model efficiency coefficient (EF) statistics were calculated. Different contributions to the overall mean square error was decomposed, using a regression-based method.
Results and Discussion: The results indicated that compared to the WAVE I, WAVE II, WCALC, ERBS, and ESRA models, the calibrated TM model had the best performance to disaggregate daily air temperature with a EF of 0.9775 to 0.9924. Compared to air temperature disaggregation models with an arbitrary value for the time of maximum and minimum air temperature, the models in which the above mentioned times are described as a function of sunrise and/or sunset had better performance in describing the diurnal variations of the air temperature. HUM III model (based on cosinusoidal disaggregation of daily actual vapour pressure) had the best performance to disaggregate daily dew point, actual vapour pressure, and relative humidity with an EF of 0.7266 to 0.8896. In addition, subdaily wind speeds were predicted with an EF of 0.3357 to 0.6300. The results showed high agreement between daily and sum-of-subdaily solar radiation (with an EF of 0.9801 to 0.9729). The use of the WAVE II and HUM II (based on linear disaggregation of relative humidity) models can be recommended for the regions with no subdaily weather data needed for calibration of the weather data disaggregation models. The results indicate the need for calibration of Green and Kozek model for disaggregation of the daily wind speed at different regions.
J. heidary; Sh. Ghorbani Dashtaki; F. Raiesi; Pejman tahmasebi
Abstract
Annual fires might change many soil physical properties in semi steppe rangeland.The objective of this study was to investigate the impact of fire on soil physical properties and soil water infiltration parameters in semi-steppe rangeland of Karsanak region in Chaharmahal and Bakhtiari province. Therefore, ...
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Annual fires might change many soil physical properties in semi steppe rangeland.The objective of this study was to investigate the impact of fire on soil physical properties and soil water infiltration parameters in semi-steppe rangeland of Karsanak region in Chaharmahal and Bakhtiari province. Therefore, several sites were chosen which were affected by fire at three, two and one years prior to this study (i.e. 2008, 2009 and 2010, respectively). Soil water infiltration was measured using tension infiltrometer in 54 points of the study sites. Since the soil samples were taken from to depth (0-10 cm and 15-25 cm) of each site, the numbers of soil samples for laboratory analysis were 108. Independent t-test and principle component analysis (PCA) was used to assess the difference between the measured properties at the burned and control sites. The results showed that aggregates stability coefficients (MWD and GMD) in the surface layer significantly reduced in 1 and 2 years after fire compared with control areas. Water dispersible clay (WDC) and bulk density significantly increased in surface layer of all burned areas compared with control areas. Saturation hydraulic conductivity significantly decreased in burned areas in 1, 2 and 3 years after. The results showed that annual fires occurs have meny negative effects on soil physical properties cause to shallow, low water retention capacity and high risk of erosion in semi steppe rangeland.
Farzin Parchami-Araghi; seyed majid mirlatifi; Shoja Ghorbani Dashtaki; Adnan Sadeghi-Lari
Abstract
Introduction: Subdaily estimates of reference evapotranspiration (ETo) are needed in many applications such as dynamic agro-hydrological modeling. The ASCE and FAO56 Penman–Monteith models (ASCE-PM and FAO56-PM, respectively) has received favorable acceptance and application over much of the world, ...
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Introduction: Subdaily estimates of reference evapotranspiration (ETo) are needed in many applications such as dynamic agro-hydrological modeling. The ASCE and FAO56 Penman–Monteith models (ASCE-PM and FAO56-PM, respectively) has received favorable acceptance and application over much of the world, including the United States, for establishing a reference evapotranspiration (ETo) index as a function of weather parameters. In the past several years various studies have evaluated ASCE-PM and FAO56-PM models for calculating the commonest hourly or 15-min ETo either by comparing them with lysimetric measurements or by comparison with one another (2, 3, 5, 9, 10, 11, 16, 17, 19). In this study, sub-daily ET o estimates made by the ASCE-PM and FAO56-PM models at different timescales (1-360 min) were compared through conduction of a computational experiment, using a daily to sub-daily disaggregation framework developed by Parchami-Araghi et al. (14).
Materials and Methods: Daily and sub-daily weather data at different timescales (1-360 min) were generated via a daily-to-sub-daily weather data disaggregation framework developed by Parchami-Araghi et al. (14), using long-term (59 years) daily weather data obtained from Abadan synoptic weather station. Daily/sub-daily net long wave radiation (Rnl) was estimated through 6 different approaches, including using two different criteria for identifying the daytime/nighttime periods : 1) the standard criteria implemented in both ASCE-PM and FAO56-PM models and 2) criterion of actual time of sunset and sunrise in combination with 1) estimation of clear-sky radiation (Rso) based on the standard approach implemented in both ASCE-PM and FAO56-PM models (1st and 2nd Rnl estimation approaches, respectively), 2) integral of the Rso estimates derived via a physically based solar radiation model developed by Yang et al. (25), YNG model, for one-second time-steps (3rd and 4th Rnl estimation approaches, respectively), and 3) integral of the calculated Rnl based on Rso estimates derived via YNG model for one-second time-steps (5th and 6th Rnl estimation approaches, respectively). The capability of the two models for retrieving the daily ETo was evaluated, using root mean square error RMSE (mm), the mean error ME (mm), the mean absolute error ME (mm), Pearson correlation coefficient r (-), and Nash–Sutcliffe model efficiency coefficient EF (-). Different contributions to the overall error were decomposed using a regression-based method (7).
Results and Discussion: Results showed that during the summer days, 24h sum of sub-daily radiation and aerodynamic components of ETo and the estimated ETo derived from both models were in a better agreement with the respective daily values. The reason for this result can be attributed to the nighttime value of cloudiness function (f) and the longer nighttime during the cold seasons. Because the nighttime values for f are equal the f value at the end of the previous daylight period until the next daylight period. The difference between sub-daily ETo derived from the ASCE-PM and FAO56-PM models during the day and night was highly dependent on the wind speed. In case of both models, daily aerodynamic component of ETo (ETod,aero) were reproduced more efficiently, compared to radiation component (ETod,rad). Except in the case of 6th Rnl estimation approach, FAO56-PM model (with a mean model efficiency (MEF) of 0.9934 to 0.9972) had better performance in reproducing the daily values of ETo (ETod), compared to ASCE-PM model (with a MEF of 0.9910 to 0.9970). The agreement between 24h sum and daily values of aerodynamic component had a lower sensitivity to the adopted time-scale, compared to the radiation component. Compared to the FAO56-PM model the performance of the ASCE-PM model in reproducing the ETod,rad, ETod,aero and ETod had higher sensitivity to the approach utilized for calculation of Rnl and hence, to the uncertainty of net radiation. Results showed that a smaller time step does not necessarily leads to an improvement in agreement between 24h sum of subdaily and daily values of ETo. Deficiency of the standard daytime/nighttime identification criteria resulted in a higher daily averaged daytime (1.3831 to 1.6753 h) used in cloudiness function calculations, compared to the respective value used in calculations of the radiation and aerodynamic components. In order to estimate the sub-daily ETo under climatic condition of the studied region, the use of ASCE-PM model based on the 6th Rnl estimation approach, (ASCE-PM)6, with a MEF of 0.9970 is preferred, compared to other studied alternatives. Another advantage of the (ASCE-PM)6 and (FAO56-PM)6 models is their computational efficiency in case of their implementation in hydrological models.
D. Baharlooi; S. Ghorbani Dashtaki; B. Khalil Moghadam; Mahdi Naderi; P. Tahmasebi
Abstract
Introduction: The detachment process can be conceptually divided in two sub-processes included aggregate breakdown (Le Bissonnais, 1996) and movement initiation of breakdown products(Kinnell, 2005). soil detachment depends on raindrop size and mass(Elison, 1944; Bisal, 1960), drop velocity(Elison, 1944; ...
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Introduction: The detachment process can be conceptually divided in two sub-processes included aggregate breakdown (Le Bissonnais, 1996) and movement initiation of breakdown products(Kinnell, 2005). soil detachment depends on raindrop size and mass(Elison, 1944; Bisal, 1960), drop velocity(Elison, 1944; Bisal, 1960), intensity rainfall (Ting et al, 2008), kinetic energy (Kinnell, 2003; Fernandez- Raga et al, 2010), runoff depth(Torri et al, 1987; Kinnell,1991 and 2005), crop covers(Bancy, 1994; Ghahremani et al, 2011), wind speed( Erpul et al, 2000) and experimental area (cup size) (Leguedois et al, 2005; Luk, 1979; Torri and poesen, 1988). Many of studies have been conducted to evaluate the relationship between splash and slope (Bryan, 1979; Torri and Poesen, 1992; Wan et al, 1996).Torri and Poesen (1992) expressed that in steep slope the gravity force adds to the drop detaching force and decreases of soil resistance, consequently increases splash erosion rate with increasing slope. Soil splash erosion is also strongly influenced by soil properties including soil particles size distribution (Mazurak and Mosher, 1968; Legout et al, 2005; fan and li, 1993), soil shear strength(Cruse and Larson, 1977; Al-Durrah and Bradford,1981; Ekwue and ohi; 1990 ), soil cohesion(Torri et al, 1987), soil organic matter content and aggregate size (Ekwue and Maiduguri, 1991; Qinjuan et al, 2008), soil aggregates stability(Qinjuan et al, 2008), surface crust (Qinjuan et al, 2008).
Fire, play an important role in splash erosion. The absence of vegetation cover in disturbed lands accelerates splash erosion rates by as much as several folds compared to undisturbed sites (Lal, 2001; Thomaz and luiz, 2012).The detachment of soil particles by splash depends on several raindrop characteristics, including raindrop size and mass, drop velocity, kinetic energy, and water drop impact angle (Sharma et al., 1993; Singer and Le Bissonnais, 1998; Cruse et al., 2000, Bhattacharyya et al., 2010). Detachment rate is strongly influenced by soil properties, including soil texture and thickness of the water layer at the soil surface (De Ploey and Savat, 1968; Moss and Green, 1983; Sharma et al., 1991; Kinnell, 1991, Jomaa et al., 2010), soil strength, bulk density, cohesion, soil organic matter content, moisture content, infiltration capacity (Nearing et al., 1988; Owoputi, 1994; Morgan et al., 1998, Planchon et al., 2000, Ghahramani et al., 2011), soil initial water content, surface compaction and roughness (Planchon et al., 2000), the nature of soil aggregates and crust, porosity, capacity of ionic interchange, and clay content (Poesen and Torri, 1988). Several studies have shown that splash detachment rate is mainly related to surface rock fragments in soils with sparse vegetation cover (Jomaa et al., 2012). The present study was conducted to investigate the effects of fire on splash erosion and some erosion depended properties in semi-steppe rangeland of Karsanak region in Chaharmahal and Bakhtiari province which affected by man-made fire during 2008, 2009, 2010 and 2011.
Materials and Methods: Soil samples were obtained on 2012 from the mentioned regions (8 samplesfrom the burned area and 8 samples as a control (unburned) in the adjacent burned area) from 0-7 cm depth. Splash erosion under simulated rainfall intensity of 2 mm per minute was measured using multivariate splash cup apparatus considering the slope of 5 and 25 degree. Soil pH, soil electrical conductivity, equivalent calcium carbonate, soil organic matter, sand size fraction particulate organic matter (SSF POM), mean weight diameter and, geometric mean diameter of aggregates, percent of macro and micro-aggregates, percent of clay, silt, sand, water dispersible clay and soil bulk density were measured. Statistical data analysis was performed by t-test at 5% level.
Results Discussion: The results showed that soil splashing increased significantly in treatment 1 year after the fire in both slope 5 and 25 degree and in treatment 2 year after the fire in slope 25 degree. The amounts of increase in soil splashing compared to control treatment were 22, 24 and 15 percent in treatment 1 year after fire in slope 5 and 25 degree and in treatment 2 years after the fire in slope of 25 degree respectively. Comparison of the total soil splash on slopes of 25 degree at 1, 2, 3 and 4 years after the fire, showed a significant increase in the level of five percent relative to the slope of 5 degree at 1, 2, 3 and 4 years after the fire. The other measured soil properties (except equivalent calcium carbonate) was affected by fire. Also, the differences between many of the mentioned properties in the first 2 years after the fire was significant compared with the control area, but they have been reached to the initial values in the third and fourth years after the fire.
Conclusion: Time was shown to be effective factor inrecovering soil propertiesin Karsanak region of Chaharmahal and Bakhtiari province which affected by man-made fire during 2008, 2009, 2010 and 2011. Fire accelerates splash erosion rates by as much as several folds compared to control in this area.
S. Mirzaee; S. Ghorbani Dashtaki; H. Khodaverdiloo
Abstract
Introduction: The infiltration process is one of the most important components of the hydrologic cycle. Quantifying the infiltration water into soil is of great importance in watershed management. Prediction of flooding, erosion and pollutant transport all depends on the rate of runoff which is directly ...
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Introduction: The infiltration process is one of the most important components of the hydrologic cycle. Quantifying the infiltration water into soil is of great importance in watershed management. Prediction of flooding, erosion and pollutant transport all depends on the rate of runoff which is directly affected by the rate of infiltration. Quantification of infiltration water into soil is also necessary to determine the availability of water for crop growth and to estimate the amount of additional water needed for irrigation. Thus, an accurate model is required to estimate infiltration of water into soil. The ability of physical and empirical models in simulation of soil processes is commonly measured through comparisons of simulated and observed values. For these reasons, a large variety of indices have been proposed and used over the years in comparison of infiltration water into soil models. Among the proposed indices, some are absolute criteria such as the widely used root mean square error (RMSE), while others are relative criteria (i.e. normalized) such as the Nash and Sutcliffe (1970) efficiency criterion (NSE). Selecting and using appropriate statistical criteria to evaluate and interpretation of the results for infiltration water into soil models is essential because each of the used criteria focus on specific types of errors. Also, descriptions of various goodness of fit indices or indicators including their advantages and shortcomings, and rigorous discussions on the suitability of each index are very important. The objective of this study is to compare the goodness of different statistical criteria to evaluate infiltration of water into soil models. Comparison techniques were considered to define the best models: coefficient of determination (R2), root mean square error (RMSE), efficiency criteria (NSEI) and modified forms (such as NSEjI, NSESQRTI, NSElnI and NSEiI). Comparatively little work has been carried out on the meaning and interpretation of efficiency criteria (NSEI) and its modified forms used to evaluate the models.
Materials and Methods: The collection data of 145 point-data of measured infiltration of water into soil were used. The infiltration data were obtained by the Double Rings method in different soils of Iran having a wide range of soil characteristics. The study areas were located in Zanjan, Fars, Ardebil, Bushehr and Isfahan provinces. The soils of these regions are classified as Mollisols, Aridisols, Inceptisols and Entisols soil taxonomy orders. The land use of the study area consisted of wheat, barley, pasture and fallow land.The parameters of the models (i.e. Philip (18), Green and Ampt (3), SCS (23), Kostiakov (6), Horton (5), and Kostiakov and Lewis (11) models) were determined, using the least square optimization method. All models were fitted to experimental infiltration data using an iterative nonlinear regression procedure, which finds the values of the fitting parameters that give the best fit between the model and the data. The fitting process was performed using the MatLab 7.7.0 (R2008b) Software Package. Then, the ability of infiltration of water into soil models with the mean of coefficient of determination (R2), root mean square error (RMSE), efficiency criteria(NSEI) and modified forms (such as NSEjI, NSESQRTI,NSElnI and NSEiI) were determined and goodness of criteria was compared for the selection of the best model.
Results and Discussion: The results showed the mean of RMSE for all soils cannot always be a suitable index for the evaluation of infiltration of water into soil models. A more valid comparison withNSEI, NSEjI, NSESQRTI, NSElnI indices indicated that these indices also cannot apparently distinguish among the infiltration models for the estimation of cumulative infiltration. These indices are sensitive to the large amount of data. The NSEiI index with giving more weight to infiltration data in shorter times was selected as the most appropriate index for comparing models. According to the NSEiI index, Kostiakov and Lewis, Kostiakov, SCS, Philip, Horton, and Green and Ampt models were the best models in approximately 72.42, 44.83, 26.9, 53.11, 11.73 and 1.0 percent of soils, respectively.
Conclusion: The results of this study indicated that the ability of modified forms of NSE indices in evaluation of infiltration of water into soil models depend on the influence of models from infiltration data values in different time series. This encourages us to be cautious on the application and interpretation of statistical criteria when evaluating the models.
Keywords: Error, Statistical criteria, Infiltration water into soil
F. Parchami Araghi; seyed majid mirlatifi; Sh. Ghorbani Dashtaki; M. Vazifehdoust; A. Sadeghi Lari
Abstract
Introduction: Subdaily estimates of reference evapotranspiration (ET o) are needed in many applications such as dynamic agro-hydrological modeling. However, in many regions, the lack of subdaily weather data availability has hampered the efforts to quantify the subdaily ET o. In the first presented paper, ...
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Introduction: Subdaily estimates of reference evapotranspiration (ET o) are needed in many applications such as dynamic agro-hydrological modeling. However, in many regions, the lack of subdaily weather data availability has hampered the efforts to quantify the subdaily ET o. In the first presented paper, a physically based framework was developed to desegregate daily weather data needed for estimation of subdaily reference ET o, including air temperature, wind speed, dew point, actual vapour pressure, relative humidity, and solar radiation. The main purpose of this study was to estimate the subdaily ETo using disaggregated daily data derived from developed disaggregation framework in the first presented paper.
Materials and Methods: Subdaily ET o estimates were made, using ASCE and FAO-56 Penman–Monteith models (ASCE-PM and FAO56-PM, respectively) and subdaily weather data derived from the developed daily-to-subdaily weather data disaggregation framework. To this end, long-term daily weather data got from Abadan (59 years) and Ahvaz (50 years) synoptic weather stations were collected. Sensitivity analysis of Penman–Monteith model to the different meteorological variables (including, daily air temperature, wind speed at 2 m height, actual vapor pressure, and solar radiation) was carried out, using partial derivatives of Penman–Monteith equation. The capability of the two models for retrieving the daily ETo was evaluated, using root mean square error RMSE (mm), the mean error ME (mm), the mean absolute error ME (mm), Pearson correlation coefficient r (-), and Nash–Sutcliffe model efficiency coefficient EF (-). Different contributions to the overall error were decomposed using a regression-based method.
Results and Discussion: The results of the sensitivity analysis showed that the daily air temperature and the actual vapor pressure are the most significant meteorological variables, which affect the ETo estimates. In contrast, low sensitivity coefficients got for wind speed and the solar radiation. The similar patterns of ETo sensitivity coefficient to the air temperature ( ) and the air temperature (TA) showed that the extent of the seasonal variation of was mainly determined by the TA. Results showed a good agreement between daily and 24h sum of subdaily ETo derived from ASCE-PM (with an EF of 0.990 to 0.994) and FAO56-PM (with an EF of 0.992 to 0.995) models. The results showed a good generalization capability of the disaggregation models to estimate the subdaily ETo for the validation data set (Ahvaz). The 24h sum of subdaily ETo derived from both models underestimated and overestimated the daily ETo in calibration (Abadan) and validation (Ahvaz) data sets, respectively. In case of both models, the daily values of aerodynamic component of ETo were reproduced more efficiently, compared to radiation part. In case of the FAO56-PM model, the goodness of agreement between 24h sum of subdaily and daily values of aerodynamic part of the ETo showed a low sensitivity to variation of the time scale of weather data. With the increase of the time scale of the subdaily weather data, the ability of both models in retrieving the radiation component of the daily ETo was improved. Generally, there was no apparent relationship between the efficiency of the ASCE-PM and FAO56-PM models for retrieving the daily ETo and the time scale of weather data. Results showed that adoption of a smaller time step does not always leads to an improvement in the agreement between 24h sum of subdaily and daily values of ETo. For most of the studied subdaily time scales (1 to 360 min), the FAO56-PM model had better performance in retrieving the daily ETo, compared to the ASCE-PM model.
Conclusion: The results of this study showed that the developed disagregation framework was able to estimate the subdaily ET o. In this study, the promising results got in retrieving the daily ETo can be attributed mainly to the high sensitivity of ETo to the air temperature and actual vapor pressure (which were desegregated with a reasonable accuracy) and low sensitivity to the wind speed (which were desegregated with a low accuracy) and the solar radiation (which were disaggregated with a reasonable accuracy). The main reason for the absence of an apparent relationship apparent relationship between the efficiency of the ASCE-PM and FAO56-PM models for retrieving the daily ETo and the time scale of weather data can be attributed to adopted nighttime and daytime criteria in both models which is highly affected by time-scale of weather data and the estimated net long wave radiation.
F. Moradi; B. KhaliliMoghadam; S. Jafari; S. Ghorbani Dashtaki
Abstract
The objective of this study was to evaluate the long-term effects of mechanized sugarcan cultivation on some soil physical properties in several lands of Khozestan Sugarcane Agro-Industries. According to this, the experiment was carried out statistically as a randomized complete block design at 38 points ...
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The objective of this study was to evaluate the long-term effects of mechanized sugarcan cultivation on some soil physical properties in several lands of Khozestan Sugarcane Agro-Industries. According to this, the experiment was carried out statistically as a randomized complete block design at 38 points in each of Deabal-Khazaei, Amir-Kabir, Karoon and Haft-Tapeh Agro-Industries with 5, 15, 40 and 50 years service. Measured soil variables included soil texture, electrical conductivity, sodium adsorption ratio, organic matter, equivalent calcium carbonate, acidity, bulk density (BD), resistance of soil penetration (PR) at 16.82-17.96 moisture interval at two depths 0-40 and 40-80 cm and mean weight diameter (MWD) at soil surface and 40 cm depth. The results showed that BD and PR increased with numbers of years service and also, MWD increased caused by improvement soil organic matter content. The PR values increased with depth, which achieved to the greatest value at 55 to 80 depth interval. Also, results showned that the significant effect of number of years service on BD, PR and MWD, so that BD, PR and MWD with increasing the number of years service from 5 to 50 years were increased from 1.57 to 1.7 gr/cm3, 0.98 to 1.16 MPa and 0.98 to 1.76 mm at first depth and 1.58 to 1.79 gr/cm3 and 1.29 to 2.15 MPa at second depth, respectively. Whereas, non-significant change was found in MWD related to increase the number of years service at first depth.
F. Parchami-Araghi; S.M. Mirlatifi; Sh. Ghorbani Dashtaki; M.H. Mahdian
Abstract
Abstract
Infiltration process is one of the most important components of the hydrological cycle. On the other hand, the direct measurement of infiltration process is laborious, time consuming and expensive. In this study, the possibility of predicting cumulative infiltration in specific time intervals, ...
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Abstract
Infiltration process is one of the most important components of the hydrological cycle. On the other hand, the direct measurement of infiltration process is laborious, time consuming and expensive. In this study, the possibility of predicting cumulative infiltration in specific time intervals, using readily available soil data and Artificial Neural Networks (ANNs) was investigated. For this purpose, 210 double ring infiltration data were collected from different regions of Iran. Basic soil properties of the two upper pedogenic layers including initial water content, bulk density, particle-size distributions, organic carbon, gravel content (>2mm size), CaCO3 percent and soil water contents at field capacity and permanent wilting point were determined on each soil sample. The feedforward multilayer perceptron was used for predicting the cumulative infiltration at times 5, 10, 15, 20, 30, 45, 60, 90, 120, 150, 180, 210, 240, 270 minutes after the start of the infiltration test and the time of basic infiltration rate. The developed ANNs were categorized into two groups; type 1 and type 2 ANNs. For developing type 1 ANNs, the basic soil properties of the first upper soil horizon were used as inputs, hierarchically. In developing the type 2 ANNs, the available soil properties of the two upper soil horizons were used as inputs, using principal component analysis technique. Results of Reliability test for developed ANNs indicated that type 1 ANNs with a RMSE of 1.136 to 9.312 cm had the best performance in estimating the cumulative infiltration. Also, type 1 ANNs with the mean RMSD of 6.307 cm had the best performance in estimating the cumulative infiltration curve.
Keywords: Artificial Neural Networks, Cumulative Infiltration, Infiltration Process, Multilayer Perceptron
