Agriculture

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Assessment and management of long-term nitrate pollution of ground water in agriculture-dominated watersheds

Journal Title, Volume, Page: 
 Journal of Hydrology (295): 225–245. doi:10.1016/j.jhydrol.2004.03.013
Year of Publication: 
2004
Authors: 
Mohammad N. Almasri
Utah Water Research Laboratory, Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322-8200, USA
Current Affiliation: 
Department of Civil Engineering, College of Engineering, An-Najah National University, P. O. Box 7, Nablus, Palestine
Jagath J. Kaluarachchi
Utah Water Research Laboratory, Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322-8200, USA
Preferred Abstract (Original): 
The objectives of this paper are to document and evaluate regional long-term trends and occurrences of nitrate in the ground water of agricultural watersheds. In Whatcom County, Washington, elevated nitrate concentrations in ground water are of great concern. Whatcom County is recognized by heavy agricultural activities, especially an intensive dairy farm industry. Historical nitrate concentration data from 1990 to 2000 were compiled from different agencies and assembled into a single composite database. A geographic information system was used to assess the spatial and temporal variability of nitrogen data. The analysis was conducted for the whole area as well as for individual watersheds and for different land use classes. In addition, nitrate concentration variability with descriptive parameters such as sampling depth, ground water recharge, dissolved oxygen, and on-ground nitrogen loadings was also investigated. The analysis showed that the areas with nitrate concentrations above the maximum contaminant level are areas characterized by heavy agricultural activities. The shallow surficial aquifers of the study area were found to contain high mean nitrate concentrations when compared to non-surficial aquifers. The analysis showed that high nitrate presence corresponds to areas with both high ground water recharge and high on-ground nitrogen loadings. In addition, the nitrate concentration decreased with increasing sampling depth. In general, the trend of long-term nitrate concentration remained elevated in shallow aquifers due to the persistent on-ground nitrogen loadings produced by agriculture-related land use practices. Finally, the watersheds were prioritized for management intervention, alternatives, and data monitoring based on a number of decision variables.
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Modular neural networks to predict the nitrate distribution in ground water using the on-ground nitrogen loading and recharge data

Journal Title, Volume, Page: 
Environmental Modelling and Software (20): 851–871. doi:10.1016/j.envsoft.2004.05.001
Year of Publication: 
2005
Authors: 
Mohammad N. Almasri
Department of Civil and Environmental Engineering and Utah Water Research Laboratory, Utah State University, Logan, UT 84322-8200, USA
Current Affiliation: 
Department of Civil Engineering, College of Engineering, An-Najah National University, P. O. Box 7, Nablus, Palestine
Jagath J. Kaluarachchi
Department of Civil and Environmental Engineering and Utah Water Research Laboratory, Utah State University, Logan, UT 84322-8200, USA
Preferred Abstract (Original): 
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.
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Applicability of statistical learning algorithms in groundwater quality modeling

Journal Title, Volume, Page: 
Water Resources Research (41) W05010. doi:10.1029/2004WR003608
Year of Publication: 
2005
Authors: 
Abedalrazq Khalil
Department of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State University, Logan, Utah, USA
Mohammad N. Almasri
Water and Environmental Studies Institute, An-Najah National University, Nablus, West Bank
Current Affiliation: 
Department of Civil Engineering, College of Engineering, An-Najah National University, P. O. Box 7, Nablus, Palestine
Mac McKee
Department of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State University, Logan, Utah, USA
Jagath J. Kaluarachchi
Department of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State University, Logan, Utah, USA
Preferred Abstract (Original): 
Four algorithms are outlined, each of which has interesting features for predicting contaminant levels in groundwater. Artificial neural networks (ANN), support vector machines (SVM), locally weighted projection regression (LWPR), and relevance vector machines (RVM) are utilized as surrogates for a relatively complex and time-consuming mathematical model to simulate nitrate concentration in groundwater at specified receptors. Nitrates in the application reported in this paper are due to on-ground nitrogen loadings from fertilizers and manures. The practicability of the four learning machines in this work is demonstrated for an agriculture-dominated watershed where nitrate contamination of groundwater resources exceeds the maximum allowable contaminant level at many locations. Cross-validation and bootstrapping techniques are used for both training and performance evaluation. Prediction results of the four learning machines are rigorously assessed using different efficiency measures to ensure their generalization ability. Prediction results show the ability of learning machines to build accurate models with strong predictive capabilities and hence constitute a valuable means for saving effort in groundwater contamination modeling and improving model performance.
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Analysis of Nitrate Contamination of Gaza Coastal Aquifer, Palestine

Journal Title, Volume, Page: 
J. Hydrol. Eng., 13(3), 132–140.
Year of Publication: 
2008
Authors: 
Mohammad N. Almasri
Water and Environmental Studies Institute, An-Najah National Univ., P.O. Box 7, Nablus, Palestine
Current Affiliation: 
Department of Civil Engineering, College of Engineering, An-Najah National University, P. O. Box 7, Nablus, Palestine
Said M. Ghabayen
College of Applied Engineering and Urban Planning, Univ. of Palestine, Gaza, Palestine
Preferred Abstract (Original): 
The ongoing degradation of the water quality of the Gaza Coastal Aquifer (GCA) is of a great concern for the different authorities and agencies involved in the water sector in the Gaza Strip, Palestine. The GCA is almost the only source of fresh water to over 1.5 million residents where it is utilized extensively to satisfy agricultural, domestic, and industrial water demands. The aquifer is currently being overpumped where pumping largely exceeds total recharge. In addition, manmade sources of pollution endanger the water resources supplies in the major municipalities of the Gaza Strip. Many water quality parameters in the GCA presently exceed the maximum contaminant level (MCL) of the US Environmental Protection Agency drinking water standards, especially for nitrate and chloride. This case study analyzes nitrate concentration distribution for the GCA at different levels such as land use classes and sampling depth. Nitrate concentration data from 1990 and from 2000 to 2004 were compiled and assembled into a single composite database. A geographic information system was used to assess the spatial and temporal variability of nitrate occurrences in the aquifer. Results show that the first quartile of nitrate concentration for the years 1990 and 2000–2004 exceeds the MCL. In addition, the analyses demonstrated a generally increasing trend in groundwater nitrate concentration. The areas with the most elevated nitrate concentrations are areas characterized by heavy agricultural activities and urban areas. Elevated nitrate concentrations in the GCA indicate anthropogenic contamination sources.
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Modeling nitrate contamination of groundwater in agricultural watersheds

Journal Title, Volume, Page: 
Journal of Hydrology (2007) 343, 211– 229
Year of Publication: 
2007
Authors: 
Mohammad N. Almasri
Water and Environmental Studies Institute, An-Najah National University, P.O. Box 7, Nablus, Palestine
Current Affiliation: 
Department of Civil Engineering, An-Najah National University, Palestine
Jagath J. Kaluarachchi
Department of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State University, Logan, Utah 84321-8200, USA
Preferred Abstract (Original): 
This paper presents and implements a framework for modeling the impact of land use practices and protection alternatives on nitrate pollution of groundwater in agricultural watersheds. The framework utilizes the national land cover database (NLCD) of the United State Geological Survey (USGS) grid and a geographic information system (GIS) to account for the spatial distribution of on-ground nitrogen sources and corresponding loadings. The framework employs a soil nitrogen dynamic model to estimate nitrate leaching to groundwater. These estimates were used in developing a groundwater nitrate fate and transport model. The framework considers both point and non-point sources of nitrogen across different land use classes. The methodology was applied for the Sumas–Blaine aquifer of Washington State, US, where heavy dairy industry and berry plantations are concentrated. Simulations were carried out using the developed framework to evaluate the overall impacts of current land use practices and the efficiency of proposed protection alternatives on nitrate pollution in the aquifer.
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Trends And Occurrences of Nitrate In The Groundwater of The West Bank, Palestine

Journal Title, Volume, Page: 
Applied Geography Volume 29, Issue 4, December 2009, Pages 588-601
Year of Publication: 
2009
Authors: 
Fathi M. Anayah
Utah Water Research Laboratory, Civil and Environmental Engineering, Utah State University, Logan, UT 84321, USA
Mohammad N. Almasri
College of Engineering, Department of Civil Engineering, An-Najah National University, P.O. Box 7, Nablus, West Bank, Palestine
Current Affiliation: 
Department of Civil Engineering, An-Najah National University, Palestine
Preferred Abstract (Original): 

Groundwater is the major source of water to the Palestinians. Efficient management of this resource requires a good understanding of its status. This understanding necessitates a characterization of the quality of the utilizable volumes. This paper focuses on the assessment of nitrate concentrations in the aquifers of the West Bank, Palestine. A preliminary statistical analysis is carried out for the spatial and temporal distributions of the nitrate concentrations. GIS is utilized to facilitate the analysis and to efficiently account for the spatiality of nitrate concentrations. The analysis was carried out at different spatial levels and key parameters including soil type, watersheds, depth, population, and rainfall. It is observed that elevated nitrate concentrations in the groundwater greatly coincide with increasing rainfall, particularly in the last few years. Results confirm that the annual mean nitrate concentration in the Western groundwater basin has an increasing trend over the period from 1982 to 2004 indicating its vulnerability to contamination. This result can be attributed to the agricultural activities along with the high groundwater recharge. However, leaking septic and sewer systems are considerably causing nitrate contamination of groundwater in populated areas. Overall, the recommendations call for an immediate intervention to manage the quality problems in the West Bank aquifers.

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Assessment Of Intrinsic Vulnerability To Contamination For Gaza Coastal Aquifer, Palestine

Journal Title, Volume, Page: 
Journal of Environmental Management 88 (2008) 577–593
Year of Publication: 
2008
Authors: 
Mohammad N. Almasri
Water and Environmental Studies Institute, An-Najah National University, P.O. Box 7, Nablus, Palestine
Current Affiliation: 
Department of Civil Engineering, An-Najah National University, Palestine
Preferred Abstract (Original): 
Gaza coastal aquifer (GCA) is the major source of fresh water for the 1.5 million residents of Gaza Strip, Palestine. The aquifer is under deteriorating quality conditions mainly due to the excessive application of fertilizers. The intrinsic vulnerability of GCA to contamination was assessed using the well-known DRASTIC method. Detailed analysis of the intrinsic vulnerability map of GCA was carried out and did consider different relationships between the vulnerability indices and the on-ground nitrogen loadings and land use classes. In addition, correlation between vulnerability values and the nitrate concentrations in GCA was studied. Based on the vulnerability analysis, it was found that 10% and 13% of Gaza Strip area is under low and high vulnerability of groundwater contamination, respectively, while more than 77% of the area of Gaza Strip can be designated as an area of moderate vulnerability of groundwater contamination. It was found that the density of groundwater sampling wells for nitrate concentration is high for the moderate and high vulnerability zones. The highest first quartile, median, mean, and third quartile of nitrate concentrations are reported in the high vulnerability zones. Results of sensitivity analysis show a high sensitivity of the high vulnerability index to the depth to water table.
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Optimal Planning Of Wastewater Reuse Using The Suitability Approach: A Conceptual Framework For The West Bank, Palestine

Journal Title, Volume, Page: 
Desalination 252 (2010) 11–18
Year of Publication: 
2010
Authors: 
Mohammad N. Almasri
Department of Civil Engineering, College of Engineering, An-Najah National University, P.O. Box 7, Nablus, Palestine
Current Affiliation: 
Department of Civil Engineering, An-Najah National University, Palestine
Laurie S. McNeill
Department of Civil and Environmental Engineering and Utah Water Research Laboratory, Utah State University,4110 Old Main Hill, Logan, UT 84322, USA
Preferred Abstract (Original): 
Recently, wastewater reuse is receiving a great deal of focus and interest among planners and decision makers in the West Bank, Palestine. This interest in wastewater reuse is motivated by the shortage in water resources accessibility due to the unstable political situation in the region. Much of the recent dispute that took place at the national level and among the stakeholders and planners revolved around issues related to the priorities of wastewater reuse in terms of location implementation of reuse schemes. The paper illustrates the conceptual framework for developing such a map and elaborates on the factors that dictate map development. Examples of such factors are discussed. The paper’s outcomes show that the development of the map requires a multi-disciplinary expertise and the work necessitates the collaboration among experts from different fields.
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