scholarly journals Object Based Modelling for the Irrigation Suitability using Hydrogeochemical Parameters and Land use Dynamics in the Lower Ganga

Author(s):  
Mohd Sayeed Ul Hasan ◽  
Abhishek Kumar Rai

Abstract The north Indian Ganga basin is one of the densely populated basins of the world. Most agricultural and industrial contaminants drained throughout the river length are likely to be accumulated in the lower part of the Ganga basin. We used ten derived irrigation suitability parameters, which are obtained from 495 sampling points locations, besides using long term climate data (GLDAS_NOAH025_M) using “Technique for Order of Preference by Similarity to Ideal Solution” (TOPSIS) model to get the irrigation suitability map. Multi-Criteria Decision Making (MCDM) using TOPSIS helps make the best choices from the available finite number of alternatives based on their ranking. The obtained entropy weight for irrigation suitability parameters such as Electrical Conductivity (Ec), Sodium Adsorption Ratio (SAR), Magnesium Hardness (MH), Sodium Percent (Na%), Total Hardness (TH), Kelly’s ratio (KR), Permeability Index (PI), Chloride concentration (Cl−), Groundwater Level Fluctuation (GWLF), and lang factor (Df) are found to be 0.08, 0.14, 0.02, 0.02, 0.04, 0.08, 0.01, 0.32, 0.29 and 0.01 respectively. We find that SAR, Cl−, and GWLF controls the water quality for irrigation in the Lower Ganga basin since these parameters have relatively higher entropy weights (more than 0.10). The results obtained from the computed performance index or the closeness coefficient show that the area percent having very good, good, and very poor groundwater quality in the Lower Ganga basin is 34.67%,42.36%, and 22.97%, respectively. The LULC change pattern indicates that the percentage change of water and agricultural land was -11.96 and -0.86%, whereas an increase in the settlement area of 131.42% for the period between 2000 and 2015.

2020 ◽  
pp. 1370-1382
Author(s):  
Saad Muhi Towfik ◽  
Adnan Jassam Hammadi

Zubair area is located at the extreme part of the south of Iraq and represents the southern part of the western desert, bounded by the north latitudes 30o05'-30o25' and east longitudes 47o30'- 47◦55'. Groundwater is a major natural resource in the study area because no perennial river exists. Groundwater from twenty wells in the study area were analyzed in order to determine some of chemical variables such as major cations (Ca+2, Mg+2 ,Na+ ,K+ ) and major anions (CL- ,SO4-2 ,HCO3- ,CO3-2 ,NO3-) along with several physical variables such as hydrogen ion concentration (pH) , total dissolved solids (TDS), and electrical conductivity (EC).  Hydro-chemical analysis showed that the groundwater of the study area is excessively mineralized, depending on the relation between EC and mineralization. Depending on total hardness (TH), all samples were with very hard water. High chloride concentration in the groundwater of the study area may be an indicator of pollution by sewage and agriculture fertilizers. The increase in flow length of the groundwater in the study area would change the water quality from bicarbonate to sulfate and chloride.   The predominant cations recorded are calcium and magnesium along with chloride from the anions, so that the water type is Ca-Mg-CL for most samples. The water wells studied are not suitable for drinking purposes of humans.  Depending on TDS and EC values, the water samples are not suitable for irrigation according to FAO 1997 classification. However, the results also revealed an excellent water class depending on Na percentage (Na%) and EC according to Todd 1980 classification for irrigation water. Also, an excellent water class (S1) for agriculture was recorded depending on SAR classification of Subramain, 2005.


2019 ◽  
Vol 1 (2) ◽  
pp. 303-323 ◽  
Author(s):  
Imzahim A. Alwan ◽  
Hussein H. Karim ◽  
Nadia A. Aziz

In this study, GIS-based Multi-Criteria Decision Approach (MCDA) is used to identify suitable locations to use groundwater for irrigation purposes in Salah-Al-Din Governorate, 180 km to the North of Baghdad, capital of Iraq republic. Various criteria are adopted including Electrical Conductivity (EC), Power of Hydrogen (pH), Sodium percentage (Na%), Sodium Adsorption Ratio (SAR), Magnesium Adsorption Ratio (MAR), Kelly’s Ratio (KR), climate factor, aquifer thickness, and aquifer elevation. Three datasets are integrated to produce the suitability model, including geophysical data, groundwater wells data and satellite-based climate data. The criteria layers are assessed using the multi-criteria decision approach by combining them together using the weighted overlay function in ArcGIS 10.5. Appropriate weights assigned and integrated into GIS to create the groundwater suitability map for irrigation. Finally, the suitability of the study area for irrigation purposes with its percent to the total area is classified into three classes according to the set criteria used for this purpose: high suitability (35.41%), low suitability (44.22%), and unsuitable/excluded (20.37%).


2020 ◽  
Vol 12 (1) ◽  
pp. 1497-1511
Author(s):  
Alexey Naumov ◽  
Varvara Akimova ◽  
Daria Sidorova ◽  
Mikhail Topnikov

AbstractDespite harsh climate, agriculture on the northern margins of Russia still remains the backbone of food security. Historically, in both regions studied in this article – the Republic of Karelia and the Republic of Sakha (Yakutia) – agricultural activities as dairy farming and even cropping were well adapted to local conditions including traditional activities such as horse breeding typical for Yakutia. Using three different sources of information – official statistics, expert interviews, and field observations – allowed us to draw a conclusion that there are both similarities and differences in agricultural development and land use of these two studied regions. The differences arise from agro-climate conditions, settlement history, specialization, and spatial pattern of economy. In both regions, farming is concentrated within the areas with most suitable natural conditions. Yet, even there, agricultural land use is shrinking, especially in Karelia. Both regions are prone to being affected by seasonality, but vary in the degree of its influence. Geographical location plays special role, and weaknesses caused by remoteness to some extent become advantage as in Yakutia. Proximity effect is controversial. In Karelia, impact of neighboring Finland is insignificant compared with the nearby second Russian city – Saint Petersburg.


Author(s):  
Yongxiang Zhang ◽  
Ruitao Jia ◽  
Jin Wu ◽  
Huaqing Wang ◽  
Zhuoran Luo

Groundwater is an important source of water in Beijing. Hydrochemical composition and water quality are the key factors to determine the availability of groundwater. Therefore, an improved integrated weight water quality index approach (IWQI) combining the entropy weight method and the stochastic simulation method is proposed. Through systematic investigation of groundwater chemical composition in different periods, using a hydrogeochemical diagram, multivariate statistics and spatial interpolation analysis, the spatial evolution characteristics and genetic mechanism of groundwater chemistry are discussed. The results show that the groundwater in the study area is weakly alkaline and low mineralized water. The south part of the study area showed higher concentrations of total dissolved solids, total hardness and NO3−-N in the dry season and wet season, and the main hydrochemical types are HCO3−-Ca and HCO3−-Ca-Mg. The natural source mechanism of the groundwater chemical components in Chaoyang District includes rock weathering, dissolution and cation exchange, while the human-made sources are mainly residents and industrial activities. Improved IWQI evaluation results indicate that water quality decreases from southwest to northeast along groundwater flow path. The water quality index (WQI) method cannot reflect the trend of groundwater. Sensitivity analysis indicated that the improved IWQI method could describe the overall water quality reliably, accurately and stably.


2007 ◽  
Vol 135 (6) ◽  
pp. 2168-2184 ◽  
Author(s):  
Gregory L. West ◽  
W. James Steenburgh ◽  
William Y. Y. Cheng

Abstract Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.


Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1459
Author(s):  
Edouard Pignède ◽  
Philippe Roudier ◽  
Arona Diedhiou ◽  
Vami Hermann N’Guessan Bi ◽  
Arsène T. Kobea ◽  
...  

One way to use climate services in the case of sugarcane is to develop models that forecast yields to help the sector to be better prepared against climate risks. In this study, several models for forecasting sugarcane yields were developed and compared in the north of Ivory Coast (West Africa). These models were based on statistical methods, ranging from linear regression to machine learning algorithms such as the random forest method, fed by climate data (rainfall, temperature); satellite products (NDVI, EVI from MODIS Vegetation Index product) and information on cropping practices. The results show that the forecasting of sugarcane yield depended on the area considered. At the plot level, the noise due to cultivation practices can hide the effects of climate on yields and leads to poor forecasting performance. However, models using satellite variables are more efficient and those with EVI alone may explain 43% of yield variations. Moreover, taking into account cultural practices in the model improves the score and enables one to forecast 3 months before harvest in 50% and 69% of cases whether yields will be high or low, respectively, with errors of only 10% and 2%, respectively. These results on the predictive potential of sugarcane yields are useful for planning and climate risk management in this sector.


2021 ◽  
Vol 940 (1) ◽  
pp. 012045
Author(s):  
K Marko ◽  
D Sutjiningsih ◽  
E Kusratmoko

Abstract The increase in built-up land and the decrease in vegetated land due to human activities have worsened watershed health from time to time. This study aims to assess the watershed’s health and changes every ten years based on the percentage of vegetated land cover except agricultural land in the Upper Citarum watershed, West Java. Land cover information was obtained from the processing of Landsat imagery in 1990, 2000, 2010, and 2020 based on remote sensing using the supervised classification method. The watershed health level is determined by calculating the percentage of vegetated land cover of 173 catchments. The results show that the area of the vegetated land cover decreased from 1990 to 2000, then increased from 2000 to 2010, and decreased again from 2010 to 2020. Changes in the area of vegetated land in each period of the year affect the health level of the watershed in a spatiotemporal manner. Although these changes occur in a fluctuating manner, the number of unhealthy catchments in the Upper Citarum watershed is increasing, especially in the Ci Kapundung sub-watershed in the north and Ci Sangkuy in the south.


2020 ◽  
Author(s):  
Pawan Thapa

Abstract Background: Soil erosion causes topsoil loss, which decreases fertility in agricultural land. Spatial estimation of soil erosion essential for an agriculture-dependent country like Nepal for developing its control plans. This study evaluated impacts on Dolakha using the Revised Universal Soil Loss Equation (RUSLE) model; analyses the effect of Land Use and Land Cover (LULC) on soil erosion. Results: The soil erosion rate categorized into six classes based on the erosion severity, and 5.01% of the areas found under extreme severe erosion risk (> 80 Mg ha-1yr-1) addressed by decision-makers for reducing its rate and consequences. Followed by 10 % classified between high and severe range from 10 to 80 Mg ha-1yr-1. While 15% and 70% of areas remained in a moderate and low-risk zone, respectively. Result suggests the area of the north-eastern part suffers from a high soil erosion risk due to steep slope. Conclusions: The result produces a spatial distribution of soil erosion over Dolakha, which applied for conservation and management planning processes, at the policy level, by land-use planners and decision-makers.


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