ABSTRACT
This study analyses long-term (1982-2014) estimates of evapotranspiration (ET) over four major river basins of India with the primary objective of understanding the factors controlling its space-time variability. Here we utilize terrestrial water storage change (TWSC) estimates, computed from WaterGAP Global Hydrology Model (WGHM) simulations, in monthly water balance computations to obtain the best available estimates of long-term ET for the study region. Trend analysis shows significant increase in annual ET over Ganga (2.72 mm/year) and Krishna (3.90 mm/year) River Basins, while in Godavari and Mahanadi River Basins the observed trends are insignificant. The relative contribution of potential factors (represented by precipitation, soil moisture, temperature and Normalized Difference Vegetation Index (NDVI)) that affect the variability of monthly ET is assessed using Hierarchical Partitioning Analysis (HPA). Results reveal that ET variance is largely controlled by the availability of water (represented by precipitation and soil moisture) in all the river basins. Precipitation (soil moisture) accounts for 65% (16%), 70% (20%), 77% (15%) and 67% (18%) of the variability in monthly ET over the Ganga, Godavari, Krishna and Mahanadi River Basins, respectively. Similarly, highest contributions from precipitation are also observed in annual scale variations of ET in all the river basins. Multiple regression analysis performed to assess the overall influence of controlling variables demonstrate that precipitation, soil moisture, temperature and NDVI explain 84% (Ganga), 86% (Godavari), 91% (Krishna) and 82% (Mahanadi) of variations observed in monthly ET over the respective basins. Results presented in this study have major implications for the understanding of ET variability, appropriateness and discrepancies in different ET products and compliment the contemporary efforts of extending GRACE-based ET estimates in space and time.
ABSTRACT
BACKGROUND: Low/middle-income countries need a large-scale improvement in the quality of care (QoC) around the time of childbirth in order to reduce high maternal, fetal and neonatal mortality. However, there is a paucity of scalable models. METHODS: We conducted a stepped-wedge cluster-randomised trial in 15 primary health centres (PHC) of the state of Haryana in India to test the effectiveness of a multipronged quality management strategy comprising capacity building of providers, periodic assessments of the PHCs to identify quality gaps and undertaking improvement activities for closure of the gaps. The 21-month duration of the study was divided into seven periods (steps) of 3 months each. Starting from the second period, a set of randomly selected three PHCs (cluster) crossed over to the intervention arm for rest of the period of the study. The primary outcomes included the number of women approaching the PHCs for childbirth and 12 directly observed essential practices related to the childbirth. Outcomes were adjusted with random effect for cluster (PHC) and fixed effect for 'months of intervention'. RESULTS: The intervention strategy led to increase in the number of women approaching PHCs for childbirth (26 vs 21 women per PHC-month, adjusted incidence rate ratio: 1.22; 95% CI 1.17 to 1.28). Of the 12 practices, 6 improved modestly, 2 remained near universal during both intervention and control periods, 3 did not change and 1 worsened. There was no evidence of change in mortality with a majority of deaths occurring either during referral transport or at the referral facilities. CONCLUSION: A multipronged quality management strategy enhanced utilisation of services and modestly improved key practices around the time of childbirth in PHCs in India. TRIAL REGISTRATION NUMBER: CTRI/2016/05/006963.
