Climate risk management for water in semi–arid regions

Andrew W Robertson,Arumugam Sankarasubramanian,Koen M J Verbist,Walter Baethgen,Francisco De Assis De Souza Filho,Upmanu Lall,Paul Block

doi:10.1186/2194-6434-1-12

Abstract

Background: New sources of hydroclimate information based on forecast models and observational data have the potential to greatly improve the management of water resources in semi-arid regions prone to drought. Better management of climate-related risks and opportunities requires both new methods to develop forecasts of drought indicators and river flow, as well as better strategies to incorporate these forecasts into drought, river or reservoir management systems. In each case the existing institutional and policy context is key, making a collaborative approach involving stakeholders essential. Methods: This paper describes work done at the IRI over the past decade to develop statistical hydrologic forecast and water allocation models for the semi arid regions of NE Brazil (the “Nordeste”) and central northern Chile based on seasonal climate forecasts. Results: In both locations, downscaled precipitation forecasts based on lagged SST predictors or GCM precipitation forecasts exhibit quite high skill. Spring-summer melt flow in Chile is shown to be highly predictable based on estimates of previous winter precipitation, and moderately predictable up to 6 months in advance using climate forecasts. Retrospective streamflow forecasts here are quite effective in predicting reductions in water rights during dry years. For the multi-use Oros reservoir in NE Brazil, streamflow forecasts have the most potential to optimize water allocations during multi-year low-flow periods, while the potential is higher for smaller reservoirs, relative to demand. Conclusions: This work demonstrates the potential value of seasonal climate forecasting as an integral part of drought early warning and for water allocation decision support systems in semi-arid regions. As human demands for water rise over time this potential is certain to rise in the future.

Highlights

New sources of hydroclimate information based on forecast models and observational data have the potential to greatly improve the management of water resources in semi-arid regions prone to drought
Downscaling of precipitation forecasts over Chile for dryland management Verbist et al (2010) (Verbist et al 2010) investigated the seasonal predictability of total seasonal rainfall total, daily rainfall frequency, and mean daily rainfall intensity on wet days at the station scale over the the Coquimbo region, using station rainfall data obtained from Chilean Water Authority (DGA)
canonical correlation analysis (CCA) was used to downscale these seasonal rainfall summary statistics directly, while a large ensemble of daily rainfall sequences was simulated at each station using the nonhomogeneous hidden Markov model (NHMM), from which the rainfall summary statistics were calculated a posteriori

Summary

Introduction

New sources of hydroclimate information based on forecast models and observational data have the potential to greatly improve the management of water resources in semi-arid regions prone to drought. Water scarcity in semi-arid regions having only one rainy season per year is a serious problem especially in developing countries. Seasonal climate forecasts, where they are skillful, provide a potential mechanism to manage drought in rainfed areas, and to better manage water allocation and reservoir operations. This paper describes approaches developed at the IRI in two semi-arid regions of South America, Central Chile, and NE Brazil covering these three aspects. The central Chile case study Climate variability can have serious social impacts in semiarid regions, especially for farmers who depend on rain-fed agriculture and on livestock production based on natural vegetation. Over USD2.6 million were spent during the severe drought of 2007 to support affected families and farmers as they repair damage, recover degraded soils, and increase irrigation programs (MINAGRI 2008)

Methods

Results

Conclusion