Asia is the region most vulnerable to climate change and India is ranked as one of the most climate vulnerable countries in the world, frequently affected by natural disasters. In this study, we investigated the impact of drought on crop productivity, farmer’s employment and income. The difference-in-difference model (DID) and stepwise multiple linear regression (MLR) were employed to quantify the impact of adopting climate resilient technologies (CRTs) on farm household income during a drought. The factors influencing farm incomes were analyzed using MLR. The study used survey data collected from the drought prone district of Telangana, India. Sixty farmers each from a village adopted under the National Innovations in Climate Resilient Agriculture (NICRA) program and a control village were interviewed. Primary data on the socio-economic characteristic of farmers, cropping pattern, income composition, productivity of major crops, employment and climate resilient interventions adopted by farmers were collected using a well-structured schedule. The results reveal that income crop cultivation was the major contributor to household income (60%) followed by livestock rearing. Farmers reported that droughts decreased the income from crops by 54 per cent and income from livestock rearing by 40 per cent. The farmers belonging to the climate resilient village had 35 per cent higher incomes compared to those in the control village and it was estimated to be Rs. 31,877/farm household/year during droughts using the DID estimate. Farm size, livestock possession, adoption of CRTs and investment in agriculture were the determining factors influencing farm income. Thus, farmers especially in drought prone regions need to be encouraged and supported to adopt cost effective, location specific climate resilient technologies.

A long-term field experiment was conducted at Hayathnagar Research Farm (HRF) of ICAR-Central Research Institute of Dryland Agriculture with the objectives to assess the effect of soil management practices viz tillage, residue application and N levels on soil phosphorus fractions, their interrelationships among themselves, impact on soil P availability pool, crop yields and P uptake. The results of the study clearly indicated that the long-term use of tillage, application of residues and N levels had a significant effect on all the P fractions in soils, except that water-soluble phosphorus (WSP) was not significantly influenced by the tillage practices. The Tillage x Residue x Nitrogen (T × R × N) significantly influenced the reductant soluble phosphorus (RSP) and total phosphorus (TP); however, the remaining P fractions were not influenced significantly. Among the combination of soil management treatments, conventional tillage (CT)+ Gliricidia loppings @ 2 tha⁻¹ (GL) + N level @ 90 kg ha⁻¹ (N90) (CTGLN90) gave the highest sorghum grain yield (1432 kg ha⁻¹) and P uptake (14.20 kg P ha⁻¹). Among the treatment combinations, the order of superiority of treatments in terms of castor yield and P uptake was: CT+ sorghum stover @ 2t ha⁻¹ (SS) + N90 (CTSSN90) (1788 kg ha⁻¹, 11.94 kg P ha⁻¹) > Minimum Tillage (MT) + sorghum stove @2 t ha⁻¹ (SS) + N level @ 90 kg ha⁻¹ (N90) (MTSSN90) (1761 kg ha⁻¹, 14.24 kg P ha⁻¹), respectively. Significant coefficients of multiple determination obtained from regression equations developed between sorghum crop yield and P fractions (R² = 0.726, p = .05) and sorghum P uptake and P fractions (R² = 0.620, p = .05) highlighted the importance of these fractions in influencing the crop yield and P uptake. Similarly, castor yield (R² = 0.748, p = .05) and P uptake (R² = 0.783) were significantly influenced by the P fractions. The results of the present study will be useful in understanding the effect of soil management practices on the status of P fractions and their contribution toward P uptake and crop yields.

Watershed development and its management are dynamic with new challenges and complexities, rendering difficulties in laying out a proper development plan. There is a need for an accurate process to assess the progress of implementation. Its assessment and evaluation need a holistic approach through reliable methods. Increasing the number of indigenous remote sensing satellites, reasonable pricing of indigenous satellite data and trained human resources have further facilitated the application of remote sensing for watershed management. In this study, a cluster of five watersheds, three in Telangana State (Mangalagudem, Rampur, Chilkepalli) and two in Andhra Pradesh (R.N. Palle, Nathiobanagari Palle-II) were taken up for watershed evaluation study. A detailed methodology for the impact evaluation of watersheds using remote sensing and geographical information system (GIS) is presented in this paper. Post classification comparison of pre-and post-implementation satellite imagery for watershed is being used for impact evaluation. Land use classification was done using SOI toposheet of 1:25,000 scale and LISS- IV (MS) remote sensing imagery. Results clearly show that interventions to check soil erosion and water run-off in a watershed mode increased Rabi cropped area up to 61 per cent and Kharif cropped area up to 22 per cent in all the watersheds. There was about a 47 per cent decrease in the extended fallow area in Nathiobanagari Palle-II watershed. Thus, interventions for checking soil erosion and runoff lead to the area's sustainable development in all the evaluated watersheds.