Papers by Bijan Ghahraman
Irrigation and Drainage, 2004
One partial solution to the problem of ever-increasing demands on our water resources is optimal ... more One partial solution to the problem of ever-increasing demands on our water resources is optimal allocation of available water. A non-linear programming (NLP) optimization model with an integrated soil water balance was developed. This model is the advanced form of a previously ...
Conventionally, drought analysis has been limited to single drought category. Utilization of mode... more Conventionally, drought analysis has been limited to single drought category. Utilization of models incor- porating multiple drought categories, can relax this limitation. A copula-based model is proposed, which uses meteorological and hydrological drought characteristics to assess drought events for ultimate man- agement of water resources, at small scales, i.e., sub-watersheds. The chosen study area is a sub-basin located at Karkheh watershed (western Iran), with five raingauge stations and one hydrometric station, lo- cated upstream and at the outlet, respectively, which represent 41-year of data. Prior to drought analysis, time series of precipitation and streamflow records are investigated for possible dependency/significant trend. Considering semi-arid nature of the study area, boxplots are utilized to graphically capture the rainy months, which are used to evaluate the degree of correlation between streamflow and precipita- tion records via nonparametric correlations. Time scales of 3- and 12-month are considered, which are used to study vulnerability of early vegetation establishment and long-term ecosystem resilience, respec- tively. Among four common goodness of fit (GOF) tests, Anderson–Darling is found preferable for defining copula distribution functions through GOF measures, i.e., Akaike and Bayesian information criteria and normalized root mean square error. Furthermore, a GOF method is proposed to evaluate the uncertainty associated with different copula models using the concept of entropy. A new bivariate drought modeling approach is proposed through copulas. The proposed index named standardized precipitation-streamflow index (SPSI) unlike common indices which are used in conjunction with station data, can be applied on a regional basis. SPDI is compared with widely applied streamflow drought index (SDI) and standard- ized precipitation index (SPI). To assess the homogeneity of the dependence structure of SPSI regionally, Kendall- τand upper tail coefficient relation is investigated for all stations located within the region. Ac- cording to results, SPSI similar to nonparametric multivariate standardized drought index (NMSDI) was able to detect both onset of droughts dominated by precipitation as is similarly indicated by SPI and persistence of droughts dominated by streamflow as is similarly indicated by SDI. It also captures dis- cordant case of normal period precipitation with dry period streamflow and vice versa. This makes SPSI a powerful tool for estimating a more practical and realistic drought condition. Finally, combination of severity–duration–frequency (SDF) of drought events through copulas resulted in SDF curves that can be used to obtain the recurrence of extreme droughts and assess drought related ecosystem failure or to aid in optimization of water resources allocation. Results indicated that the newly proposed index (SPSI) is able to represent two main characteristics of meteorological and hydrological drought (drought onset and persistency) and also providing an accurate estimation of the recurrence interval of extreme droughts. The procedures can be used to undertake proactive water resource management and planning to assure water security and sustainable agriculture and ecosystem survival for regions experiencing extreme droughts.
In hydrological models, soil conservation services (SCS) are one of the most widely used procedur... more In hydrological models, soil conservation services (SCS) are one of the most widely used procedures to calculate the curve number (CN) in rainfall run-off simulation. Recently, another new CN accounting procedure has been mentioned, namely the plant evapotranspiration (ET) method or simply known as the plant ET method. This method is embedded in the Soil and Water Assessment Tool (SWAT) model which has been developed for watersheds covered by shallow soils or soils with low storage characteristics. It uses antecedent climate and plant evapotranspiration for calculation of daily curve number. In this study, the same method had been used to simulate the daily stream flow for Roodan watershed located in the southern part of Iran. The watershed covers 10570 km 2 and its climate is arid to semi-arid. The modeling process required data from digital elevation model (DEM), land use map, and soil map. It also required daily meteorological data which were collected from weather stations from 1988 to 2008. Other than that, the Sequential Uncertainty Fitting-2 (SUFI-2) algorithm was utilized for calibration and uncertainty analysis of daily stream flow. Criteria of modeling performance were determined through the Nash-Sutcliffe and coefficient of determination for calibration and validation. For calibration, the values were reported at 0.66 and 0.68 respectively and for validation; the values were 0.51 and 0.55. Moreover, percentiles of absolute error between observed and simulated data in calibration and validation period were calculated to be less than 21.78 and 6.37 (m 3 /s) for 95% of the data. The results were found to be satisfactory under the climatic conditions of the study area.
In this study, a new approach, which we called pseudo-continuous, to develop pedotransfer functio... more In this study, a new approach, which we called pseudo-continuous, to develop pedotransfer functions (PTFs) for predicting soil-water retention with an artificial neural network (ANN) was introduced and tested. It was compared with ANN PTFs developed using traditional point and parametric approaches. The pseudo-continuous approach has a continuous performance, i.e. it enables to predict water content at any desirable matric potential, but without the need to use a specific equation, such as the one by van Genuchten. Matric potential is considered as an input parameter, which enables to increase the number of samples in the training dataset with a factor equal to the number of matric potentials used to determine the water retention curve of the soil samples in the dataset. Generally, the pseudo-continuous functions performed slightly better than the point and parametric functions. The root mean square error (RMSE) of the pseudo-continuous functions when considering local data for training and testing, and with both bulk density and organic matter as extra input variables on top of sand, silt and clay content, was 0.027 m 3 m À3 compared to 0.029 m 3 m À3 for both the point and parametric PTF. The increased number of samples in the training phase and the selection of matric potential as an input variable enabling to predict water content at any desired matric potential are the most important reasons why pseudo-continuous functions would need more intention in the future. Uniformity in the training and test dataset was shown to be important in deriving PTFs. We finally recommend the use of pseudo-continuous PTFs for further improvement and development of PTFs, in particular when datasets are limited.
Production functions (PFs) are practical tools for not only irrigation scheduling but also in eco... more Production functions (PFs) are practical tools for not only irrigation scheduling but also in economic analysis as a mathematical relationship between relative grain yield and factors like evapotranspiration, irrigation water and salinity. This study was carried out in the Mashhad region of Iran during cropping years 2010 and 2011 to evaluate the performances of two data mining methods, decision tree and neural network, for deriving PFs of spring wheat under simultaneous drought and salinity stress compared with four well known regression-based PFs. The four well known PFs were: Jensen-PF (Jensen, 1968), Minhas-PF , modified Stewart-PF , and Nairizi-PF . Heading and flowering were the most sensitive growth stages followed by the stem elongation and booting. Salinity stress also affected grain yield and therefore was an important parameter for deriving PFs. In general, all the PFs were in agreement concerning the sensitivity of spring wheat to water stress. The neural network-based PF performed the best with a root mean square error equal to 44.27 g m À2 while the decision tree-based PF ranked fourth out of six in terms of accuracy. The most important advantage of the neural network-based PF was the flexible number of input parameters.
Paper: MODELING SOIL DEPTH TEMPERATURE BY USING METEOROLOGICAL PARAMETERS
Soil Science Society of America Journal
Scaling methods allow a single solution to Richards’ equation (RE) to suffi ce for numerous speci... more Scaling methods allow a single solution to Richards’ equation (RE) to suffi ce for numerous specifi c cases of water fl ow in unsaturated soils. During the past half-century, many such methods were developed for similar soils. In this paper, a new method is proposed for scaling RE for a wide range of dissimilar soils. Exponential-power (EP) functions are used to reduce the dependence of the scaled RE on the soil hydraulic properties. To evaluate the proposed method, the scaled RE was solved numerically considering two test cases: infi ltration into relatively dry soils having initially uniform water content distributions, and gravity-dominant drainage occurring from initially wet soil profi les. Although the results for four texturally different soils ranging from sand to heavy clay (adopted from the UNSODA database) showed that the scaled solution were invariant for a wide range of fl ow conditions, slight deviations were observed when the soil profi le was initially wet in the inf...
Probable Maximum Precipitation for 24 Hour Duration over Four Central Provinces in Iran
World Environmental and Water Resources Congress 2009, 2009
Paper: ESTIMATION OF 24-H PROBABLE MAXIMUM PRECIPITATION BY USING DIFFERENT STATISTICAL APPROACHES FOR NORTH-EAST OF IRAN
Paper: PERFORMANCE EVALUATION OF SCALING METHODS OF RICHARDS’EQUATION IN INFILTRATION MODELING IN A WATERSHED (CASE STUDY: MARGHMALEK WATERSHED)
Paper: EVALUATION OF WATER SALINITY AND SODICITY EFFECT ON DIFFUSIVITY AND UNSATURATED HYDRAULIC CONDUCTIVIY
REGIONALIZATION OF RAINFALL TEMPORAL PATTERN IN IRAN
Paper: PERFORMANCE EVALUATION OF SOME INTERNAL PEDOTRANSFER FUNCTIONS TO PREDICTION SOIL MOISTURE RETENTION CURVE
Paper: APPLICATION OF TIME SERIES ANALYSIS FOR FORECASTING OF MASHHAD MONTHLY AND ANNUAL RAINFALL
Paper: A COMPARATIVE STUDY FOR DETERMINATION OF PMP BY SOME STATISTICAL METHODS IN ATRAK WATERSHED, IRAN
Paper: RESERVOIR OPERATING USING FUZZY INFERENCE SYSTEM AND CLUSTERING (CASE STUDY: ILANJOGH DAM)
Paper: ESTIMATION OF SOIL SALINITY PROFILE IN TABRIZ IRRIGATION AND DRAINAGE NETWORK USING SALTMOD AND ANN MODELS
SENSITIVITY ANALYSIS AND UNCERTAINTY PARAMETERS AFFECTING IN THE ESTIMATION OF REFERENCE EVAPOTRANSPIRATION IN MODELS WITH DIFFERENT MATHEMATICAL STRUCTURE
Uploads
Papers by Bijan Ghahraman