Prioritising land and water interventions for climate smart villages (CSVs) Background. Land and Water interventions (LWI)

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1 Background Prioritising land and water interventions for climate smart villages (CSVs) Mohammad Faiz Alam and Alok Sikka International Water Management Institute, Delhi Climate change and Agriculture Natural resources: Limited, degraded, competition One way to fight multiple challenges: Climate Smart Agriculture (CSA) CSV is a participatory model of implementing and upscaling CSA [CCAFS] Local knowledge and plans Capacity development Technologies targeting Productivity Adaptation CSA Mitigation 2 CSV interventions Land and Water interventions (LWI) CSV involves prioritizing and implementing portfolio of CSA practices Targeting multiple dimensions of climate smartness Land and Water interventions form significant part of climate smart agriculture practices portfolio Agriculture major consumer Water a main constraint Knowle dge Weather Nutrient Land and Water Land and Carbon Water Energy LWI consists of range of practice including >> Increasing agricultural productivity by increasing water availability Decrease runoff Increase recharge storage improving soil moisture increasing water use efficiency Impact of LWI interventions in the vulnerable districts of India to enhance resilience of agriculture to climate change and climate variability is well documented 3 4 1

2 Need for prioritization Existing prioritization frameworks Multiple options in LWI portfolio, however, not all LWI are climate smart everywhere Climate is different Production systems are different Soil, land management and aquifer properties are different Varying costs and economic impacts Important to understand the individual and combined impact and tradeoffs productivity, adaptation and GHGs mitigation. Many a times LWI are lumped and are implemented based on stakeholder consultation and perceived benefits Due to limited capacity to develop complex Data intensive hydrological models for that area biases CCAFS/IWMI-ITC stakeholder consultation emphasised priortisation Multiple prioritisation frameworks exist four phase prioritization framework [Andrieu, et al. (2017)] consensus-driven decision support framework targetcsa by Brandt, et al. (2017) climate smart agriculture rapid appraisal (CSA-RA) by Mwongera, et al. (2017) Data driven (SWAT, CROP yield models) [Webber et al., 2014; Shirsath et al., 2017] Limitations overall CSV/CSA > Do not target LWI specifically limited quantitative impact analysis data intensive and involves models require subject matter expertise Need of simple, easily replicable and conceptually robust framework that can help stakeholders and implementing organisations to prioritise LWI individually and in combination. 5 6 How Practices integrated Simulates water budget, Soil moisture, runoff, GWR Crop water requirements Category Practices Average yield (FAO yield response function) Determine impact of interventions on water balance >> Crop yields >> production Prioritise based on available resources, feasibility, impact and cost effectiveness Storage (supply) Soil and moisture (S&M) Demand Farm pond, Groundwater recharge, stop dam Broad bed furrow, No tillage, crop mulching, bunds/barriers Drip, sprinkler, land levelling 7 8 2

3 Indicators for prioritisation Application of tool and village in Madhya Pradesh ITC project village sites Productivity Δ Yield Irrigated area Drought resilience Climate smart indicators Emissions Cost and Benefits Δ IRR DR Δ GHG BCR Parameter Rainfall Average annual 1141 mm Drought Year( 2002): 886 mm Average annual 1189 mm Drought Year (2002): 1206 mm Soil Black cotton soil Black cotton soil Land use (CN) Village area: 283 ha Crop land: 259 ha Village area: 643 ha Crop land: 591 ha Crop Kharif (June- October): Soybean, ; Rabi (November March):, Chickpea Kharif (June- October): Soybean, ;Rabi (November March):, Chickpea Irrigated 93 ha, Groundwater: 88 ha 111 ha, Groundwater: 84 ha 9 10 Scenarios Results: Water Balance Scenario Scenario 1 (FP) Scenario 2 (SD) Supply Farm pond Stop dam Demand S&M Monsoon dependent ( > 90% rain, runoff, recharge) Making rainfed agriculture highly vulnerable to any deficit Drought: Deficit in July and excess in August High runoff and minimal recharge in drought seasons Scenario 3 (GWR) Scenario 4 (SI) Scenario 5 (LL) Scenario 6 (BBF) Scenario 7 (NT) Scenario 8 (FP+SI) Scenario 9 (GWR + SI) Scenario 10 (FP+SI+BBF) Scenario 11 (FP+SI+BBF) Groundwater recharge Farm pond Groundwater recharge GOOD FEATURE Farm pond GOOD FEATURE Groundwater recharge GOOD FEATURE Land levelling MODERATE FEATURE MODERATE FEATURE Sample Text MODERATE FEATURE Sample Text MODERATE FEATURE BBF BAD FEATURE No BAD tillage FEATURE BBF BAD FEATURE BBF BAD FEATURE Normal Drought Average Drought Annual Monsoon Annual Monsoon Annual Monsoon Annual Monsoon Rainfall % % % % Runoff % % % % Recharge % % % % ET % % % % 12 3

4 Results: Water Balance Crop yields (Normal year) Monsson dependent ( > 90% rain, runoff, recharge) Making rainfed agriculture highly vulnerable to any deficit Drought: Deficit in July and excess in August High runoff and minimal recharge in drought seasons 100 % 100 % Chickpea 19.8 % 100 % 100 % 100 % 21.1 % 100 % Normal Drought Average Drought Annual Monsoon Annual Monsoon Annual Monsoon Annual Monsoon 100 % 100 % Chickpea 13.9 % 71.7 % Rainfall % % % % Runoff % % % % Recharge % % % % ET % % % % 100 % 100 % 16.7 % 66.3 % Rainfed Irrigated Rainfed Irrigated Kharif Rabi Crop yields (Deficit year) Impact Indicators: 81.7 % 83.4 % Chickpea 16.4 % 45.5% 16.7 % 47.3% 85 % 86.4 % 70.6 % 68.0 % Chickpea 6.5 % 6.5 % 76.6 % 78.2 % 10.1 % % Rainfed Irrigated Rainfed Irrigated Kharif Rabi % % Scenario 1(FP) 4.0% 70.4% -7.4% -16.9% 1.4 Scenario 2(SD) 0.4% 37.8% -0.7% -22.4% 0.3 Scenario 3(GWR) 3.3% 64.0% -6.1% -20.0% 3.4 Scenario 4(SI) 2.0% 52.5% -3.9% -22.4% 2.3 Scenario 5(LL) 1.1% 44.3% -2.2% -22.7% 7.7 Scenario 6(BBF) 3.0% 49.5% -5.7% -20.8% 5.9 Scenario 7(NT) 3.6% 54.7% -6.7% -20.2% NA Scenario 8(FP+SI) 6.5% 92.5% -11.7% -15.4% 1.7 Scenario 9(GWR+SI) 5.8% 86.3% -10.5% -19.0% 3.1 Scenario 10(FP+SI+BBF) 9.7% 111.0% -16.6% -13.3% 2.2 Scenario 11 (GWR+ SI+BBF) 9.0% 104.9% -15.6% -16.7%

5 Impact Indicators: Impact Indicators: % % Scenario 1(FP) 4.0% 70.4% -7.4% -16.9% 1.4 Scenario 2(SD) 0.4% 37.8% -0.7% -22.4% 0.3 Scenario 3(GWR) 3.3% 64.0% -6.1% -20.0% 3.4 Scenario 4(SI) 2.0% 52.5% -3.9% -22.4% 2.3 Scenario 5(LL) 1.1% 44.3% -2.2% -22.7% 7.7 Scenario 6(BBF) 3.0% 49.5% -5.7% -20.8% 5.9 Scenario 7(NT) 3.6% 54.7% -6.7% -20.2% NA Scenario 8(FP+SI) 6.5% 92.5% -11.7% -15.4% 1.7 Scenario 9(GWR+SI) 5.8% 86.3% -10.5% -19.0% 3.1 Scenario 10(FP+SI+BBF) 9.7% 111.0% -16.6% -13.3% 2.2 Scenario 11 (GWR+ SI+BBF) 9.0% 104.9% -15.6% -16.7% % Scenario 1(FP) 4.5% 0.0% -8.2% -34.3% 1.5 Scenario 2(SD) 0.5% 0.0% -1.0% -37.6% 0.3 Scenario 3(GWR) 4.2% 0.0% -7.7% -35.8% 3.6 Scenario 4(SI) 1.9% 0.0% -3.7% -38.3% 1.1 Scenario 5(LL) 1.1% 0.0% -2.2% -38.3% 3.9 Scenario 6(BBF) 3.7% 0.0% -6.9% -34.9% 6.9 Scenario 7(NT) 4.4% 0.0% -8.2% -33.8% NA Scenario 8(FP+SI) 6.5% 0.0% -11.7% -33.6% 1.3 Scenario 9(GWR+SI) 6.2% 0.0% -11.2% -35.5% 2.1 Scenario 10(FP+SI+BBF) 9.8% 0.0% -16.8% -30.0% 1.8 Scenario 11 (GWR+ SI+BBF) 9.5% 0.0% -16.4% -31.4% Impact Indicators: Conclusions % Scenario 1(FP) 4.5% 0.0% -8.2% -34.3% 1.5 Scenario 2(SD) 0.5% 0.0% -1.0% -37.6% 0.3 Scenario 3(GWR) 4.2% 0.0% -7.7% -35.8% 3.6 Scenario 4(SI) 1.9% 0.0% -3.7% -38.3% 1.1 Scenario 5(LL) 1.1% 0.0% -2.2% -38.3% 3.9 Scenario 6(BBF) 3.7% 0.0% -6.9% -34.9% 6.9 Scenario 7(NT) 4.4% 0.0% -8.2% -33.8% NA Scenario 8(FP+SI) 6.5% 0.0% -11.7% -33.6% 1.3 Scenario 9(GWR+SI) 6.2% 0.0% -11.2% -35.5% 2.1 Scenario 10(FP+SI+BBF) 9.8% 0.0% -16.8% -30.0% 1.8 Scenario 11 (GWR+ SI+BBF) 9.5% 0.0% -16.4% -31.4% 2.7 Stakeholder workshop perception ranking Broadly aligns with ranking Adds value Standalone interventions have limited impact Demand interventions only when supply is there Supply and demand interventions S&M interventions impact both rainfed and irrigated area High BCR Integrated practices have maximum impact Cost is proportionate There is limit to resilience Need for other safety net, risk transfer mechanism Significant opportunity to reduce GHG intensity Important to realise and account

6 Future/ongoing work Including practices that includes other states where land, soil and cropping pattern is different Framework for upscaling results Based on clustering of villages based on their characteristics of climate, land use, cropping pattern and performance on CSA Thank you Interface and user testing Conclusion (contd.) Crop yields (Normal year) CCAFS organised stakeholder workshop in Madhya Pradesh to rank practices suited. Results broadly aligns well with stakeholders inclination towards supply augmentation measures of rainwater harvesting, demand side measure of sprinkler and soil moisture activities of broad bed furrow and conservation tillage. Added value of our results: can differentiate between practices Can overcome biases providing impact of combination of practices in comparison to ranking of individual practices by stakeholders. Give impact of village scale whereas stakeholder s perspective, especially of farmers, could be biased by impact of farm level. Thus, pre and post integration of analysis

7 Crop yields (Drought year) What we do Simple excel based spreadsheet tool Requiring easily accessible data Easily replicable Gives individual or combined interventions impact on village under CSA objectives Excel tool uses water budgeting to give an idea on: Current water availability and demand Potential of different interventions Impact and cost-benefits of interventions Also, to know the limit!