Water is the most important resource; it is utilized largely in agricultural production and is fundamental to ensuring global food security. This study aims to assess sustainable water management interventions and their impact on the farm economy. To increase water productivity, the most important adaptations that have been proposed are high-efficiency irrigation systems, drought-resistant varieties, the substitution of water-intensive crops with less water-demanding crops, the mulching of soil, zero tillage, and all on-farm operations that can save water, especially ground water. The recent analysis utilized farm survey data from 469 representative farmers along with secondary statistics. The data were collected via a multi-stage sampling technique to ensure the availability of representative farm populations based on a comprehensive site selection criterion. The TOA-MD model estimates the adoption rate of a proposed adaptation based on net farm returns. The impact of high-efficiency irrigation systems and the substitution of high delta crops for low delta crops had a positive impact on net farm returns and per capita income, and a negative impact on farm poverty in the study area. It is recommended that policymakers consult farmer representatives about agricultural and water-related issues so that all the policies can be implemented properly.

Agricultural intensification is increasing global demand for water, with groundwater especially susceptible given its year-round reliability. Climate change impacts on groundwater recharge exacerbate uncertainties for future access and use, especially for large aquifers across alluvial plains such as the Indus Basin of Pakistan. To generate better understanding of climate change impacts on groundwater balances in such contexts, we used MODFLOW 2005 to quantify the groundwater budget of the Northern Rohri Canal Command Area under RCP 4.5 and 8.5 climatic scenarios, while also taking climatic regionalisation into account. Under a baseline scenario, total annual pumping in the northern Rohri command was estimated to be 3.619 billion cubic metres (BCM), and the total net loss in storage over the simulation period from October 2010 to April 2014 was estimated at 1.244 BCM per year. By 2047, net decline in storage is projected to more than double to 2.185 per year under RCP 4.5 scenario and 2.214 under RCP 8.5. Our estimates suggest that a sustainable yield across the command area should be managed at approximately 3 ± 0.3 BCM per year to ensure sufficient adaptive reserves of groundwater for access during times of drought and inadequate surface supply, while also reducing waterlogging impacts from high watertables. This first-time estimate of sustainable yield provides irrigation system managers with an overall guide from which divisional-scale measures to achieve the goal can be identified through stakeholder engagement.

In a water-scarce country such as Pakistan, rainfall is the third-largest source of freshwater. In most of the urban cities of the country, rainwater is mixed with sewerage and is rendered useless for managed aquifer recharge purposes. Therefore, this study investigates the rainfall potential for managed aquifer recharge in Lahore (Pakistan). The present research was designed and conducted by the Irrigation Research Institute (IRI). Three different sites were selected for rainwater sample collection across the study area (Lahore), ranging from urban to rural areas. The rainwater samples were collected and divided into three categories (direct capture, rooftop runoff, street runoff). For longer rainfall events, the effect of time on the quality of the collected rainwater samples was also studied. Spatiotemporal trends of turbidity, pH, electrical conductivity, total dissolved solids, carbonates, bicarbonates, chloride, calcium, magnesium, and hardness in the collected rainwater samples were investigated. In terms of TDS, results indicated that directly captured rainwater is most suitable for managed aquifer recharge (TDS < 50 ppm), followed by rooftop runoff (TDS < 100 ppm). In addition, the quality of rainwater samples collected at the rural site was comparatively better. Moreover, the quality of rainwater samples improved after the initial ten minutes. All in all, this study concludes that direct capture of rainwater is the most suitable option for managed aquifer recharge.

Managed aquifer recharge (MAR) is a complex and hidden process of storing surplus water under the ground surface and extracting it as, when and where needed. Evaluation of the success of any MAR project is challenging due to uncertainty in estimating the hydrogeological characteristics of the subsurface media. This paper demonstrates the use of a groundwater model (MODFLOW) to evaluate a new, large-scale regional MAR project in the agricultural heartland in Punjab, Pakistan. In this MAR project, flood waters have been diverted to the bed of an abandoned canal, where 144 recharge wells (the wells for accelerating the recharge into the aquifer) have been constructed to accelerate the recharge to the aquifer. The model was calibrated for a period of five years from October 2015 to June 2020 on a monthly stress period and the resulting water levels were simulated till 2035. The water balance components and future response of the aquifer to different scenarios up to 2035 including with and without MAR situations are presented. The model simulations showed that MAR can contribute to the replenishment of the aquifer and its potential for the case study site to contribute significantly to the management of groundwater and to enhance supplies for intensive agriculture. It was further established that MODFLOW can help in the evaluation of effectiveness of a MAR scheme. This study is unique as it evaluates a significantly large MAR project in an area where this practice has not been developed for improving groundwater access for large scale irrigation. The model provides guidelines for decision makers in the region as well as for the global community and livelihood benefits for rural communities.

Despite growing recognition of solutions to water scarcity challenges, decision-makers across the world continue to face barriers to effective implementation of water planning, governance and management. This is evident in the cases of Lahore and Karachi in the Indus Basin in Pakistan and illustrated through the experiences of the provincial government departments and utilities. Water scarcity and associated challenges are continuing to impose significant costs on these cities, which continue to grow as water availability further declines, demand increases, water quality deteriorates, and infrastructure degrades. A team of Australian water experts was commissioned by the Australian Water Partnership to diagnose urban water challenges and identify priority actions for improved water security, in collaboration with Pakistani partners. This paper presents the outcomes of that work. This includes a synthesis of the published literature and data on the geographical, climatic, and water scarcity contexts of both Karachi and Lahore. It then identifies responses to water insecurity that have been considered or implemented in the past and the barriers that have inhibited the effectiveness of these efforts. Finally, it presents actions within five priority action areas that Pakistani stakeholders have identified as being most practical and impactful for improving water security outcomes.

The over-extraction of groundwater from thin fresh groundwater lenses is a threat to the livelihood of farmers in the Lower Indus Basin (LIB). It is essential to monitor and regulate this pumping to sustain fresh groundwater lenses. In this study, we applied a modelling approach in combination with geostatistical analysis to identify the critical locations to monitor the groundwater levels for sustaining fresh groundwater in the LIB. Our approach included four steps: (i) simulating temporal heads using a calibrated hydrogeological model; (ii) sampling monitoring locations using a hexagonal pattern of sampling; (iii) applying principal component analysis (PCA) of the temporal head observations, and selecting high scoring locations from the PCA; and (iv) minimizing the observation points to represent the water level contours. The calibrated model was able to replicate the hydro-dynamic behavior of the study area, with a root mean square of 0.95 and an absolute residual mean of 0.74 m. The hexagonal pattern of spatial sampling resulted in a 195 point network, but PCA reduced this network to 135 points and contour classification reduced it even further to 59 points. The 195, 135, and 59 point networks represented the water levels with average standard errors of 0.098, 0.318, and 0.610 m, respectively. Long-term simulations with increased pumping showed that the water levels would best be assessed by 195 monitoring points, although 135 and 59 points would represent the depleting area but would not capture the water logging area.