#1InoCotton GROW SPONSORED BY THE Exploring improvements in water management for the cotton and textile industry - results from a case study in Punjab and its contribution to achieving UN-SDGs in Pakistan 06th of May 2020, EGU2020 online Strehl, Clemens¹; Wencki, Kristina1; Weber, Frank- Andreas²; Becker, Rike¹; aus der Beek, Tim¹ and InoCotton GROW partners Federal Ministry of Education and Research 1 IWW Water Centre (IWW Rheinisch-Westfälisches Institut für Wasserforschung gGmbH), Mülheim an der Ruhr, Germany 2 FiW, Research Institute for Water and Waste Management at RWTH Aachen (FiW) e. V., Aachen, Germany#2InoCotton GROW BACKGROUND Interdisciplinary project to address water management problems in the region of Lower Chenab Canal in Punjab, Pakistan Irrigation of cotton plants as well as dyeing and finishing processes during textile production require tremendous amounts of water Work on technically, economically and institutionally feasible ways of increasing the efficiency of water use along the cotton-textile value chain in Pakistan JHANG SADAR Gojra Mungi disty KAMALIA Chenab CHINIOT FAISALABAD Lower Gugera Branch Killianwala Disty: N Kilometers 0 15 30 60 90 120 Mian Ali Branch Khurrianwala Disty Burala Branch Lower Chenab Car HAFIZABAD Upper Gugera Branch GUJRANWALA SHEKHUPURA Ravi LAHORE Rivers Khurrianwala_disty Killianwalii_disty Mungi_disty Cities Irrigation Figure: InoCotton GROW and IWW O InoCottonGROW All rights reserved 2#3InoCotton GROW PROJECT PARTS AND LINK TO SDGS ☐ Hydrological modeling of climate change scenarios to analyze water stress (see EGU2020-8144, Becker et al. 2020) Water footprint simulations Analysis of irrigation techniques and other adaptive measures (based on site visits and knowledge exchange with scientists, farmers and textile industry in Pakistan) Incorporation of hydrological modeling, water footprint simulations, water stress considerations and adaptive measures to future scenarios Analysis of interlinkages, synergies and trade-offs of adaptation scenarios with regards to UN SDGs O InoCottonGROW All rights reserved 3#4InoCotton GROW SCENARIOS TO CHANGE THE WATER MANAGEMENT (ADAPTATION) No. Title 1. Making the most of the current system Storyline Optimize existing system, maximize water efficiency in cotton production, reduce water usage for exhaust dyeing 2. Many pennies make a dollar 3. Think big 4. Regional water shifting 5. 6. Small scale technological changes, improved irrigation. practices at field level, reduce water usage for exhaust dyeing, legislation for improved effluent treatment at medium and large textile processing companies Large scale infrastructure projects in water supply and sewage disposal (e.g. lining of main canals and sewers or installation of wastewater treatment plants at central drains), reduction of water and dyes usage in exhaust dyeing Adjusted water distribution including changes in the institutional setup, controlled deficit irrigation. Regional crop shifting Incentives to modify cropping patterns Quality instead of quantity Pesticide reduction, all medium and large textile companies install functioning effluent treatment plants, penalties for non- compliance O InoCottonGROW All rights reserved#5InoCotton GROW APPROACH FOR A QUALITATIVE ANALYSIS: ADAPTATION OF THE "ICSU-METHOD" O InoCottonGROW All rights reserved Analysis based on a methodology proposed by the International Council for Science in 2019: "A Guide to SDG Interactions: From SDG Type of Scenario Scenario Scenario Scenario Scenario Scenario Targets influence 1 2 3 5 6 2.1 on +1 +1 +2 +2 +3 +2 Science to Implementation" 2.2 on +1 +1 +2 0 +1 +1 2.3 Qualitative impact on/by +1 +1 +2 +2 +2 +1 2.4 assessment on/by +2 +1 +1 +2 +2 +2 " SDG targets assumed to be 2.a on/by +1 +2 +1 +2 +1 +1 influenced by any scenario 6.1 on +1 +2 14 +2 +2 +1 +2 or having an influence on 6.2 by 0 0 0 +1 +2 0 any scenario 6.3 on/by +2 +3 +3 0 -1/+3 +3 scores: +3 = "indivisible"; 6.4 on/by +3 +2 +2 +3 +1 +2 +2="reinforcing"; 6.5 by 0 0 0 +1 +1 +1 +1 "enabling"; 6.6 on/by +2 +2 +1/-1 -1 +1 +2 0 = "consistent"; 6.a by +1 +1 +1 +1 +1 +1 -1 = "constraining"; 6.b on/by +2 +1 0 +1 +1 +1 -2 = "counteracting"; Example for SDGs #2 and #6 -3 = "cancelling". 5#6InoCotton GROW APPROACH FOR A QUANTITATIVE ANALYSIS: FROM HYDRO-MODELING TO SDG IMPACT SDG Indicator 6.4.2: Level of water stress [t=0] National scale [t=0] Regional scale [t=0] A per scenario to status quo SDG Indicator 6.4.2: Level of water stress [t=1] National scale [t=1] Regional scale [t=1] Legend: [t=0] represents point in time with no changes (status quo) [t=1] represents point in time with changes (water management scenario) Hydrological simulation of key indicators, e.g.: Ground water recharge [mm/season] Amount of irrigation water applied [mm/season] O InoCottonGROW All rights reserved 6#7InoCotton GROW APPROACH FOR A QUALITATIVE ANALYSIS: FROM WATER FOOTPRINT TO SDG IMPACT Intervention Cotton Promotion of a more flexible irrigation scheduling within Warabandi system WF Secondary Effects (relevant for SDG assessment) Reduced soil evaporation O InoCottonGROW All rights reserved Textile Promotion of drip irrigation techniques Increased dissemination of storage systems Higher application efficiency, reduced groundwater recharge Indirect effects by supporting measures above Reducing water usage (groundwater pumping), additionally energy and time savings Promotion of water-efficient machinery in textile processing Promotion of advanced dyestuff and process chemicals Reduce in groundwater pumping, ↓ additionally energy and time savings, increased COD concentration without WWT Installation and operation of Increased energy consumption, reduced effluent WWTPs in all large- and medium-size textile finishing ↓ emission concentrations to ZDHC foundational Wastewater plants Example: Effects of scenario 2 (“Many pennies make a dollar”) on the water footprint and SDGs 7#8InoCotton GROW PRINCIPLE FINDINGS The interdisciplinary approach led to several water management scenarios valuable for decision makers. All management scenarios have the potential for highly positive effects on the achievement of several SDG targets. Adaptation of the ICSU approach for SDG interactions to case level in Punjab offered a structured method to analyze interactions between high-level SDGs and regional water management changes. Highest impacts may occur with regard to water quality (#6.3) and water-use efficiency (#6.4). Side benefits became visible for food security (#2.1), energy efficiency (#7.3), upgrade of infrastructure (#9.4), sustainable management of natural resources, chemicals and wastes (#12.2 & 12.4), and waste reduction (#12.5). Nevertheless, trade-offs or negative effects might concern the protection and restoration of water- related ecosystem (#6.6), if water is regionally shifted, and marine ecosystems (#15.1-3) in case of adjusted crop cultivation. O InoCottonGROW All rights reserved 8#9InoCotton GROW www.inocottongrow.net A special thanks to our project lead: FiW, Research Institute for Water and Waste Management at RWTH Aachen (FiW) e. V. InoCotton GROW آپ کی توجہ کے لئے آپ کا شکریہ. IWW Water Centre (IWW Rheinisch-Westfälisches Institut für Wasserforschung gemeinnützige GmbH), Mülheim an der Ruhr, Germany MORITZSTRASSE 26 4576 MÜLHEIM AN DER RUHR, GERMANY PHONE: +49 (0) 208 403 03 0 IWW-ONLINE.DE/EN/ SPONSORED BY THE Federal Ministry of Education and Research The project is funded by the Federal Ministry of Education and Research (BMBF) within the framework of the funding measure "Water as a Global Resource (GROW)" 6