Irrigation Induced Salinity and Sodicity Hazards on Soil and Groundwater: An Overview of Its Causes, Impacts and Mitigation Strategies

Salinity and sodicity have been a major environmental hazard of the past century since more than 25% of the total land and 33% of the irrigated land globally are affected by salinity and sodicity. Adverse effects of soil salinity and sodicity include inhibited crop growth, waterlogging issues, groundwater contamination, loss in soil fertility and other associated secondary impacts on dependent ecosystems. Salinity and sodicity also have an enormous impact on food security since a substantial portion of the world’s irrigated land is affected by them. While the intrinsic nature of the soil could cause soil salinity and sodicity, in developing countries, they are also primarily caused by unsustainable irrigation practices, such as using high volumes of fertilizers, irrigating with saline/sodic water and lack of adequate drainage facilities to drain surplus irrigated water. This has also caused irreversible groundwater contamination in many regions. Although several remediation techniques have been developed, comprehensive land reclamation still remains challenging and is often time and resource inefficient. Mitigating the risk of salinity and sodicity while continuing to irrigate the land, for example, by growing salt-resistant crops such as halophytes together with regular crops or creating artificial drainage appears to be the most practical solution as farmers cannot halt irrigation. The purpose of this review is to highlight the global prevalence of salinity and sodicity in irrigated areas, highlight their spatiotemporal variability and causes, document the effects of irrigation induced salinity and sodicity on physicochemical properties of soil and groundwater, and discuss practical, innovative, and feasible practices and solutions to mitigate the salinity and sodicity hazards on soil and groundwater

Irrigation Induced Salinity and Sodicity Hazards on Soil and Groundwater: An Overview of Its Causes, Impacts and Mitigation Strategies

Salinity and sodicity have been a major environmental hazard of the past century since more than 25% of the total land and 33% of the irrigated land globally are affected by salinity and sodicity. Adverse effects of soil salinity and sodicity include inhibited crop growth, waterlogging issues, groundwater contamination, loss in soil fertility and other associated secondary impacts on dependent ecosystems. Salinity and sodicity also have an enormous impact on food security since a substantial portion of the world’s irrigated land is affected by them. While the intrinsic nature of the soil could cause soil salinity and sodicity, in developing countries, they are also primarily caused by unsustainable irrigation practices, such as using high volumes of fertilizers, irrigating with saline/sodic water and lack of adequate drainage facilities to drain surplus irrigated water. This has also caused irreversible groundwater contamination in many regions. Although several remediation techniques have been developed, comprehensive land reclamation still remains challenging and is often time and resource inefficient. Mitigating the risk of salinity and sodicity while continuing to irrigate the land, for example, by growing salt-resistant crops such as halophytes together with regular crops or creating artificial drainage appears to be the most practical solution as farmers cannot halt irrigation. The purpose of this review is to highlight the global prevalence of salinity and sodicity in irrigated areas, highlight their spatiotemporal variability and causes, document the effects of irrigation induced salinity and sodicity on physicochemical properties of soil and groundwater, and discuss practical, innovative, and feasible practices and solutions to mitigate the salinity and sodicity hazards on soil and groundwater

Monthly Streamflow Prediction by Metaheuristic Regression Approaches Considering Satellite Precipitation Data

In this study, the viability of three metaheuristic regression techniques, CatBoost (CB), random forest (RF) and extreme gradient tree boosting (XGBoost, XGB), is investigated for the prediction of monthly streamflow considering satellite precipitation data. Monthly streamflow data from three measuring stations in Turkey and satellite rainfall data derived from Tropical Rainfall Measuring Mission (TRMM) were used as inputs to the models to predict 1 month ahead streamflow. Such predictions are crucial for decision-making in water resource planning and management associated with water allocations, water market planning, restricting water supply and managing drought. The outcomes of the metaheuristic regression methods were compared with those of artificial neural networks (ANN) and nonlinear regression (NLR). The effect of the periodicity component was also investigated by importing the month number of the streamflow data as input. In the first part of the study, the streamflow at each station was predicted using CB, RF, XGB, ANN and NLR methods and considering TRMM data. In the second part, streamflow at the downstream station was predicted using data from upstream stations. In both parts, the CB and XGB methods generally provided similar accuracy and performed superior to the RF, ANN and NLR methods. It was observed that the use of TRMM rainfall data and the periodicity component considerably improved the efficiency of the metaheuristic regression methods in modeling (prediction) streamflow. The use of TRMM data as inputs improved the root mean square error (RMSE) of CB, RF and XGB by 36%, 31% and 24%, respectively, on average, while the corresponding values were 37%, 18% and 43% after introducing periodicity information into the model’s inputs

Trends and Non-Stationarity in Groundwater Level Changes in Rapidly Developing Indian Cities

In most of the Indian cities, around half of the urban water requirement is fulfilled by groundwater. Recently, seasonal urban droughts have been frequently witnessed globally, which adds more stress to groundwater systems. Excessive pumping and increasing demands in several Indian cities impose a high risk of running out of groundwater storage, which could potentially affect millions of lives in the future. In this paper, groundwater level changes have been comprehensively assessed for seven densely populated and rapidly growing secondary cities across India. Several statistical analyses were performed to detect the trends and non-stationarity in the groundwater level (GWL). Also, the influence of rainfall and land use/land cover changes (LULC) on the GWL was explored. The results suggest that overall, the groundwater level was found to vary between ±10 cm/year in the majority of the wells. Further, the non-stationarity analysis revealed a high impact of rainfall and LULC due to climate variability and anthropogenic activities respectively on the GWL change dynamics. Statistical correlation analysis showed evidence supporting that climate variability could potentially be a major component affecting the rainfall and groundwater recharge relationship. Additionally, from the LULC analysis, a decrease in the green cover area (R = 0.93) was found to have a higher correlation with decreasing groundwater level than that of urban area growth across seven rapidly developing cities