Abstract

The Tharpakar desert region of Pakistan supports a population approaching two million, dependent on rain-fed agriculture as the main livelihood. The almost doubling of population in the last two decades, coupled with low and variable rainfall, makes this one of the world’s most food-insecure regions. This paper examines satellite-based rainfall estimates and biomass data as a means to supplement sparsely distributed rainfall stations and to provide timely estimates of seasonal growth indicators in farmlands. Satellite dekadal and monthly rainfall estimates gave good correlations with ground station data, ranging from R = 0.75 to R = 0.97 over a 19-year period, with tendency for overestimation from the Tropical Rainfall Monitoring Mission (TRMM) and underestimation from Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) datasets. CHIRPS was selected for further modeling, as overestimation from TRMM implies the risk of under-predicting drought. The use of satellite rainfall products from CHIRPS was also essential for derivation of spatial estimates of phenological variables and rainfall criteria for comparison with normalized difference vegetation index (NDVI)-based biomass productivity. This is because, in this arid region where drought is common and rainfall unpredictable, determination of phenological thresholds based on vegetation indices proved unreliable. Mapped rainfall distributions across Tharparkar were found to differ substantially from those of maximum biomass (NDVImax), often showing low NDVImax in zones of higher annual rainfall, and vice versa. This mismatch occurs in both wet and dry years. Maps of rainfall intensity suggest that low yields often occur in areas with intense rain causing damage to ripening crops, and that total rainfall in a season is less important than sustained water supply. Correlations between rainfall variables and NDVImax indicate the difficulty of predicting drought early in the growing season in this region of extreme climatic variability. Mapped rainfall and biomass distributions can be used to recommend settlement in areas of more consistent rainfall.

Highlights

  • The Thar Desert, located to the northwest of the Indian subcontinent, is one of the largest subtropical deserts [1]

  • The study demonstrated the effective utilization of satellite-based rainfall products for spatial analysis of phenology over the Tharparkar desert region, as well as implications and policy indicators arising from the analysis

  • Both Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and Tropical Rainfall Monitoring Mission (TRMM) generally gave reliable rainfall estimates compared to ground stations, CHIRPS daily estimates were more reliable than those for TRMM and the tendency for underestimation by CHIRPS, compared to overestimation by TRMM, made CHIRPS better suited for use in a drought-prone region where overestimation may overlook serious drought periods

Read more

Summary

Introduction

The Thar Desert, located to the northwest of the Indian subcontinent, is one of the largest subtropical deserts [1]. It is regarded as the only fertile desert in the world, with a population dependent on rain-fed agriculture and livestock rearing, and it was declared by the World Food Program as the most food-insecure region of Pakistan [2]. The climate of the Thar is characterized by low and erratic rainfall, high temperature, and long spells of dry weather, which threaten agricultural livelihoods. The only continuous rain gauge station within Tharparkar (Figure 1), has 277 mm of rainfall annually, but this varies greatly from year

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call