Pakistan

The apportionment of waters of the Indus River System between the provinces of Pakistan is widely hailed as a historic agreement. This agreement (herein referred to as the Accord) was signed into effect in 1991, just over 25 years ago. The Accord lacks a clearly stated objective and hence it is difficult to review the Accord against its objective. This paper presents a detailed thematic review of the Accord and interprets the literature and data sets that have become available over the last 25 years. Although the Accord leaves room for interpretation, which is often biased to a particular perspective, an obvious starting point that has been highlighted in the literature is to improve water accounting in the Indus basin and to clarify and document the Operating Rules. Over the next 25 years, demographic change, socioeconomic change, and climate change in the Indus Basin will place this Accord under increased scrutiny.

This paper evaluates 30-year (2013–2042) projections of the selected climatic parameters in cotton/wheat agro-climatic zone of Pakistan. A statistical bias correction procedure was adopted to eliminate the systematic errors in output of three selected general circulationmodels (GCM) under A2 emission scenario. A transfer function was developed between the GCM outputs and the observed time series of the climatic parameters (base period: 1980–2004) and applied to GCM future projections. The predictions detected seasonal shifts in rainfall and increasing temperature trend which in combination can affect the crop water requirements (CWR) at different phonological stages of the two major crops (i.e. wheat and cotton). CROPWAT model is used to optimize the shifts in sowing dates as a climate change adaptation option. The results depict that with reference to the existing sowing patterns, early sowing of wheat and late sowing of cotton will favour decreased CWR of these crops.

Due to extensive groundwater development in the recent past, Pakistan now faces enormous challenges of groundwater management as it struggles to ensure food security for its rapidly growing population. These management challenges require a re-balancing of surface and groundwater monitoring objectives and approaches in the country. This article presents the current status of the groundwater monitoring and management in Pakistan. A compelling case is presented for optimization of material resources in improving groundwater level and quality data by proposing to use farmer organizations as a source of crowd sourced groundwater information. The authors showcase new methods to collect groundwater data and demonstrate use of automatic recording instruments for groundwater monitoring in a tertiary canal command area in the Pakistan’s Punjab. The results suggest that the potential for broader impact by engaging farmer organization and expanding monitoring networks is attractive. A common concern about long term deployment of automatic instruments is that the observation wells are not purged before extracting water quality samples. The authors address this concern through a field experiment by utilizing capabilities of automatic recording instruments.

The paper presents a moderate resolution imaging spectroradiometer (MODIS) time-series imagery-based algorithm for detection and mapping of seasonal and annual changes in flood extent, and tests this using the flooding of the Indus River Basin in 2010 – one of the greatest recent disasters that affected more than 25 million people in Pakistan. The algorithm was applied to produce inundation maps for 10 annual flood seasons over the period from 2000 to 2011. The MODIS flood products were validated in comparison with advanced land observing system (ALOS) sensors, which have both advanced visible and near infrared radiometer and phased array type L-band synthetic images using the flood fraction comparison method. A simple threshold method is created to cluster the data to identify the flood pixels in the imagery. Calculations are then made to estimate a flood area for each resolution. A statistical study is performed to analyze false positive and false negative rates using the ALOS sensors as ‘ground truth’. Comparison of two flood products at a grid size of 10 km resulted in the coefficient of determination range of 0.72–0.97. This research points to a relevant spatial resolution that could be effectively used to obtain accurate mapped products of the extent of the inundated area. The approach can be used to quantify the damage caused by floods.