Integrated GIS-based modelling approach for irrigation water quality suitability zonation in parts of Satluj River Basin, Bist Doab region, North India

Abstract

The groundwater is the main source for irrigation and other purposes in the alluvial plains of Punjab. The poor irrigational water quality affects the soil quality which interrupts the growth of plants impacting the agricultural production and can cause risk to human health, and thus, it is important to evaluate the water quality for irrigation uses in the agrarian regions. An integrated GIS-based modelling approach along with conventional water quality indices such as sodium adsorption ratio, per cent sodium, residual sodium carbonate, residual sodium bicarbonate, magnesium hazard, permeability index, potential salinity, Kelly's ratio, electrical conductivity, total hardness, pH and total dissolved solids was used to delineate the irrigation water quality suitability zones in parts of agricultural prolific Satluj River Basin. Analytical results revealed that groundwater of the study area is very hard and slightly alkaline in nature and the relative abundance order of major ions is Mg 2+ > Na + + K + > Ca 2+ and HCO 3 − + CO 3 2− > Cl − > SO 4 2− , respectively, for cations and anions. The weighted overlay technique was applied to generate the irrigation water quality zonation map, and results revealed that nearly 3.2% (117 sq. km) of the total area was not suitable for the irrigation water quality, whereas 85.2% (3076 sq. km) and 11.6% (421 sq. km) area fall under moderately suitable and suitable classes, respectively. The elevated level of some ions found in the shallower zone as compared to the deeper zones indicates that in addition to the geogenic factors (weathering and dissolution of aquifer materials) anthropogenic inputs such as ill agricultural practices, leaching from septic tanks and municipal waste are adversely affecting the groundwater system in the region. The results of US Salinity Laboratory's diagram showed that 42% groundwater samples fall in C3S1 (high salinity with low sodium hazard) category indicating the unsuitability for irrigation purpose due to high salinity hazard and cannot be used in soils with restricted drainage. The results of Piper and Durov diagrams revealed that Ca 2+-Mg 2+-HCO 3 − is the dominant hydrochemical facies with Mg 2+-HCO 3 − water type in the groundwater of the study area and hydrochemistry is controlled by both natural and anthropogenic factors. The bottom-up approach and involvement of locals can boost the management of water resources in the study area.

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

“…Furthermore, the aforementioned techniques to assess the water quality, Water Quality Indices (WQIs) are used to determine the quality of water, which present a useful interpretation of the quality of water used for irrigation. The individual water quality parameter is not adequate to estimate the validation of water for irrigation because it can be restrictive and may often produce inadequate performance in the evaluation [23]. The weighted score of each variable was used by several other studies to suggest a water quality index [24,25].…”

Evaluation and prediction of irrigation water quality of an agricultural district, SE Nigeria: an integrated heuristic GIS-based and machine learning approach

“…Accordingly, different weight rankings (e.g. suitable; moderately suitable; and unsuitable) (Doneen 1964;Todd 1980;Wilcox 1955;Singh et al 2019). Spatial distribution maps were then generated for each parameter by integrating the inverse distance Weighting (IDW) technique and simple kriging (SK).…”

“…All thee input parameters were assigned an equal weightage of 1 (Table 2). As proposed by Singh et al (2019), there is an equal importance for all the irrigation water quality parameters in irrigation water quality assessment. However, an observation of the results of the irrigation water quality (Table 2) revealed that some variables (e.g.…”

“…However, an observation of the results of the irrigation water quality (Table 2) revealed that some variables (e.g. MAR, SSP, PI, SAR, and KR) seemed to occur under the suitable class, hence, were not used in the weighted overlay analysis (Singh et al 2019). Therefore, to produce the irrigation zonation map, the ranks and weights of each parameter was multiplied.…”

“…The EC for groundwater varied between 78.9µS/cm and 674.1 µS/cm (mean 424.58 µS/cm). High electrical conductivity can affect the root of plants and affect soil fertility (Singh et al 2019). EC value greater than 700μS/cm of irrigational water can impede the movement of water into the root zone (Bouaroudj et al 2019).…”