An-Najah Staff

Among the most basic challenges of hydrology are the quantitative understanding  of the processes of runoff generation and prediction of flow hydrographs. Traditional techniques have been widely applied for the estimation of runoff hydrographs of gauged catchments using historical rainfall–runoff data and unit hydrographs. Such procedures are questioned as to their reliability and their application to ungauged, arid, and semiarid catchments. To overcome such difficulties, the use of physically based rainfall–runoff estimation methods such as the Geomorphologic Instantaneous Unit Hydrograph (GIUH) approach has evolved. This paper models the rainfall–runoff process of Faria catchment using the lately developed KW–GIUH. Faria catchment, located in the northeastern part of the West Bank, Palestine, is characterized as a semiarid region with annual rainfall depths ranging on average from 150 to 640 mm at both ends of the catchment. The Geographical Information System (GIS) techniques were used to shape the geomorphological features of the catchment. A GIS-based KW–GIUH hydrological model was used to simulate the rainfall–runoff process in the three sub-catchments of Faria, namely: Al-Badan, Al-Faria, and Al-Malaqi. The simulated runoff hydrographs proved that the GIS-based KW–GIUH model is applicable to semiarid regions and can be used to estimate the unit hydrographs in the West Bank catchments.

Among the most basic challenges of hydrology are the quantitative understanding  of the processes of runoff generation and prediction of flow hydrographs. Traditional techniques have been widely applied for the estimation of runoff hydrographs of gauged catchments using historical rainfall–runoff data and unit hydrographs. Such procedures are questioned as to their reliability and their application to ungauged, arid, and semiarid catchments. To overcome such difficulties, the use of physically based rainfall–runoff estimation methods such as the Geomorphologic Instantaneous Unit Hydrograph (GIUH) approach has evolved. This paper models the rainfall–runoff process of Faria catchment using the lately developed KW–GIUH. Faria catchment, located in the northeastern part of the West Bank, Palestine, is characterized as a semiarid region with annual rainfall depths ranging on average from 150 to 640 mm at both ends of the catchment. The Geographical Information System (GIS) techniques were used to shape the geomorphological features of the catchment. A GIS-based KW–GIUH hydrological model was used to simulate the rainfall–runoff process in the three sub-catchments of Faria, namely: Al-Badan, Al-Faria, and Al-Malaqi. The simulated runoff hydrographs proved that the GIS-based KW–GIUH model is applicable to semiarid regions and can be used to estimate the unit hydrographs in the West Bank catchments.

This paper presents a modeling approach based on a geographic information system (GIS) to estimate the variability of on-ground nitrogen loading and the corresponding nitrate leaching to ground water. The methodology integrates all point and nonpoint sources of nitrogen, the national land cover database, soil nitrogen transformations, and the uncertainty of key soil and land use-related parameters to predict the nitrate mass leaching to ground water. The analysis considered 21 different land use classes with information derived from nitrogen sources such as fertilizer and dairy manure applications, dairy lagoons, septic systems, and dry and wet depositions. Simulations were performed at a temporal resolution of one month to capture seasonal trends. The model was applied to a large aquifer of 376 square miles in Washington State that serves more than 100,000 residents with drinking water. The results showed that dairy manure is the main source of nitrogen in the area followed by fertilizers. It was also seen that nitrate leaching is controlled by the recharge rate, and there can be a substantial buildup of soil nitrogen over long periods of time. Uncertainty analysis showed that denitrification rate is the most influential parameter on nitrate leaching. The results showed that combining management alternatives is a successful strategy, especially with the use of nitrification inhibitors. Also, change in the land use pattern has a noticeable impact on nitrate leaching.

Artificial neural networks have proven to be an attractive mathematical tool to represent complex relationships in many branches of hydrology. Due to this attractive feature, neural networks are increasingly being applied in subsurface modeling where intricate physical processes and lack of detailed field data prevail. In this paper, a methodology using modular neural networks (MNN) is proposed to simulate the nitrate concentrations in an agriculture-dominated aquifer. The methodology relies on geographic information system (GIS) tools in the preparation and processing of the MNN input–output data. The basic premise followed in developing the MNN input–output response patterns is to designate the optimal radius of a specified circular-buffered zone centered by the nitrate receptor so that the input parameters at the upgradient areas correlate with nitrate concentrations in ground water. A three-step approach that integrates the on-ground nitrogen loadings, soil nitrogen dynamics, and fate and transport in ground water is described and the critical parameters to predict nitrate concentration using MNN are selected. The sensitivity of MNN performance to different MNN architecture is assessed. The applicability of MNN is considered for the Sumas-Blaine aquifer of Washington State using two scenarios corresponding to current land use practices and a proposed protection alternative. The results of MNN are further analyzed and compared to those obtained from a physically-based fate and transport model to evaluate the overall applicability of MNN.

Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number (CN) is a key factor in determining runoff in the SCS (Soil Conservation Service) based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems (GIS) are now being used in combination with the SCS-CN method. This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method. The West Bank, Palestine, is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region. The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments, representing arid to semi-arid catchments of Palestine.

Among the most basic challenges of hydrology are the quantitative understanding of the processes of runoff generation and prediction of flow hydrographs. Traditional techniques have been widely applied for the estimation of runoff hydrographs of gauged catchments using historical rainfall-runoff data and unit hydrographs. Such procedures are questioned for their reliability and their application to ungauged, arid and semiarid catchments. To overcome such difficulties, the use of physically based rainfall-runoff estimation methods such as the Geomorphologic Instantaneous Unit Hydrograph (GIUH) approach has evolved. This paper models the rainfall-runoff process of Faria catchment using the lately developed KW-GIUH. Faria catchment, located in the northeastern part of the West Bank, Palestine, is characterized as a semiarid region with annual rainfall depths ranging on average from 150 to 640 mm at both ends of the catchment. The Geographical Information System (GIS) techniques were used to shape the geomorphological features of the catchment. GIS-based KW-GIUH hydrological model was used to simulate the rainfall-runoff process in the three sub-catchments of Faria namely Al-Badan, Al-Faria and Al-Malaqi. The simulated runoff hydrographs proved that the GIS-based KW-GIUH model is applicable to semiarid regions and can be used to estimate the unit hydrographs in the West Bank catchments.

Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number (CN) is a key factor in determining runoff in the SCS (Soil Conservation Service) based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems (GIS) are now being used in combination with the SCS-CN method. This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method. The West Bank, Palestine, is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region. The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments, representing arid to semi-arid catchments of Palestine.