Revitalizing Traditional Water Tanks for Climate Adaptation in India

Last registered on March 24, 2024
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Pre-Trial

Trial Information

General Information

Title
Revitalizing Traditional Water Tanks for Climate Adaptation in India
RCT ID
AEARCTR-0012398
Initial registration date
January 15, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 19, 2024, 2:07 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
March 24, 2024, 3:43 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
India
Region
Bundelkhand

Primary Investigator

Name
Shweta Bhogale
Affiliation
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Aanchal Bagga
PI Affiliation
Tufts University
Contact Investigator
PI Name
Kyle Emerick
PI Affiliation
Tufts University
Contact Investigator

Additional Trial Information

Status
On going
Start date
2023-05-01
End date
2026-05-31
Keywords
Agriculture, Environment & Energy
Additional Keywords
Climate adaptation, Public goods, Water, Agricultural Productivity
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Irrigation allows farmers to adapt to heat stress or droughts. However, the threat of groundwater depletion and uneven access to irrigation make it an incomplete adaptation response. This project assesses how public goods, like water reservoirs that enhance widespread irrigation access through collecting and storing rainwater, can facilitate climate adaptation. We test the effectiveness of such tanks by studying the constraints they face from farmers' irrigation responses and other input markets like water and labor.

In the Bundelkhand region of central India, traditional tanks were constructed centuries ago to store rainwater for irrigation during the next dry season. The tanks have accumulated silt over time reducing their capacity and ability to source water in the dry season. Our intervention will deepen these tanks to improve their volume and facilitate underground drainage of harvested water. Farmers can access this water directly from the tank through pumps or increased water levels in their wells. This intervention could either equip farmers with the necessary irrigation to improve their productivity and mitigate the negative effects of climate shocks, or, it could lead farmers to undo the positive effects of the tank by disproportionately increasing water extraction as a response to the increased water supply. The effects of the tank may also be susceptible to "elite capture" through large farmers using costly equipment to monopolize the resource in the local water market. Therefore, we also evaluate how an individually targeted intervention like training on conservative and climate-robust agriculture affects the resilience, productivity, and efficiency of groundwater use. Our design tests the extent to which the training can substitute or complement the tank renovation intervention. Last, we will measure how the tank affects labor supply and demand on the farms and whether this is likely to moderate the effects of the intervention on climate adaptation.
External Link(s)

Registration Citation

Citation
Bagga, Aanchal, Shweta Bhogale and Kyle Emerick. 2024. "Revitalizing Traditional Water Tanks for Climate Adaptation in India." AEA RCT Registry. March 24. https://doi.org/10.1257/rct.12398-1.1
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Experimental Details

Interventions

Intervention(s)
There are two kinds of interventions involved:

1) Tank renovation: villages could have two kinds of structures - tanks, which are like man-made lakes/reservoirs, and ‘dohas’, which are saucer-shaped structures dug in the stream bed along its length separated into multiple, smaller water ponds by mud dams to prevent overflow. The water tanks/dohas were originally built at the foot of a hill or a natural slope to capture rainwater during the monsoon (June-September) and they formed the main source of stored water in these villages. Currently, after accumulating silt over 1000 years, the tanks/dohas have reduced volumes of water and tend to run completely dry by February/March, restricting farmers’ ability to crop and irrigate all of their cultivable lands in the dry season, and limiting the water available for domestic activities and livestock rearing. SRIJAN is engaged in renovating these tanks by digging out 8-10 ft of the silt across the whole structure which will increase its carrying capacity such that the water could last longer, ideally until the next monsoon hits.

2) Training: The training intervention involves repeated sessions with the NGO’s experts before and during the dry season (November to May) that cover different aspects of agricultural practices that can improve yields, make the crop robust to shocks, and enhance water efficiency on the farm.
Intervention Start Date
2023-06-01
Intervention End Date
2025-07-01

Primary Outcomes

Primary Outcomes (end points)
Our outcomes of interest will also span tank-level outcomes:

Water levels across different months captured through farmer reports in survey data as well as satellite imagery; water-source level outcomes: water-levels in wells owned by sample farmers across different in-person survey time points

Household-level outcomes: crop choice, irrigation practices, yield, profitability, consumption
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Input-market outcomes: the price of water, and the going agricultural wage for different tasks.

Household-level outcomes: family versus hired labour inputs for different farm tasks broken down by gender, temporary migration to urban areas during the lean season, women’s time use - especially for domestic water collection
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This project evaluates the individual and complementary effects of public and private climate adaptation tools for farmers in the context of publicly managed water reservoirs and training targeted to farmer’s individual investments. These villages could have two kinds of structures - tanks, which are like man-made lakes/reservoirs, and ‘dohas’, which are saucer-shaped structures dug in the stream bed along its length separated into multiple, smaller water ponds by mud dams to prevent overflow. The water tanks/dohas were originally built at the foot of a hill or a natural slope to capture rainwater during the monsoon (June-September) and they formed the main source of stored water in these villages. Currently, after accumulating silt over 1000 years, the tanks/dohas have reduced volumes of water and tend to run completely dry by February/March, restricting farmers’ ability to crop and irrigate all of their cultivable lands in the dry season, and limiting the water available for domestic activities and livestock rearing.

Villages were randomized into treatment groups by stratifying on state and whether they have a tank or a doha, since the effects of a doha may be more locally concentrated relative to a tank. Our design is a 2X2 RCT with the following treatment groups:
Treatment 1: 39 villages. Tanks/Dohas renovation only.
Treatment 2: 39 villages. Training only.
Treatment 3: 38 villages. Tank/Doha Renovation + Training.
Control group: 38 villages. Neither.

Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Randomization at the village level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
154
Sample size: planned number of observations
1232 (8 per village)
Sample size (or number of clusters) by treatment arms
Treatment 1: 39 villages.
Treatment 2: 39 villages.
Treatment 3: 38 villages.
Control group: 38 villages.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We use data from a recent village clustered RCT that we did with Indian rice farmers (Emerick et al., 2016). The plot-level crop yield is 2,817 kg per ha with a standard deviation of 1,354. The intra-cluster correlation (ICC) is 0.3449. This is high for the average cluster RCT, but not for agricultural outcomes which tend to be more correlated within villages. For this reason, our RCT uses 150 villages, rather than a smaller number of villages with more farmers per village. The strata fixed effects and baseline yields explain 17.9 percent of the variation in yield. We assume that we will obtain similar predictive power with our stratification and conditioning on the baseline outcome. Finally, we assume that each farmer will have 1.5 plots in the potential command area of the tank, making 12 observations per village. Using these parameters, we estimate a MDE of 433 kilograms per hectare on the pooled treatment effects. This is 0.32 standard deviations or about 15 percent of the mean yield. This seems like reasonable MDE, particularly since irrigation can be transformative. For instance, Jones et al (2021) find that irrigation increases cash profits by about 50% in Rwanda.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Tufts University IRB
IRB Approval Date
2023-04-25
IRB Approval Number
STUDY00003442
IRB Name
Institute for Financial Management and Research
IRB Approval Date
2023-04-19
IRB Approval Number
NA
Analysis Plan