Rainfall characteristics and their implications for rain-fed agriculture: a case study in the Upper Zambezi River Basin

Abstract

This study investigates rainfall characteristics in the Upper Zambezi River Basin and implications for rain-fed agriculture. Seventeen indices describing the character of each rainy season were calculated using a bias-corrected version of TRMM-B42 v6 rainfall estimate for 1998-2010. These were correlated with maize yields obtained by applying a SVATmodel. Finally, a self-organizing map (SOM) was trained to examine multivariate relationships. The results reveal a significant spatio-temporal variability of rainfall indices and yields, with a gradient from north to south. Yields greater than 1 t/ha are found to be only achievable with rainy seasons longer than 160 days. For shorter durations, the interplay of total rainfall, dry spell frequency and maximum dry/wet spell durations determines agricultural success. Using total rainfall alone or wet day frequency as estimators for yields is insufficient. Alternating wet and dry spells affect yields most negatively. The results have significance in the context of agricultural planning under changing climatic conditions and agricultural planning, as well as for the development of forecasting mechanisms.

Estimation of groundwater recharge via deuterium labelling in the semi-arid Cuvelai-Etosha Basin, Namibia

“…With the combination of tracer and soil moisture profiles, quantification of water fluxes is possible. Especially at Eenhana, we emphasize the importance of the intra-seasonal distribution of rainfall for the movement of water through the unsaturated zone and the creation of groundwater recharge in semi-arid environments, which is discussed in earlier studies [54]. From further experiments on-site, it was determined that a rainfall event as high as 60 mm did not infiltrate deeper than 40 cm on a dry soil (data not shown herein).…”

“…It is therefore crucial for recharge estimates to investigate the rainfall characteristics of the rainy season when evaluating groundwater recharge. An analysis of these characteristics according to the criteria defined in Beyer et al [54] was performed for the rainy season 2013/2014. Indicators which are believed to be related to groundwater recharge such as maximum wet spell duration, number of events above 10 mm and rainfall during the core rainy season [54] were found to be in an upper range: rainfall within the core rainy season was 615 mm, and the maximum wet spell duration equalled 22 days.…”

“…An analysis of these characteristics according to the criteria defined in Beyer et al [54] was performed for the rainy season 2013/2014. Indicators which are believed to be related to groundwater recharge such as maximum wet spell duration, number of events above 10 mm and rainfall during the core rainy season [54] were found to be in an upper range: rainfall within the core rainy season was 615 mm, and the maximum wet spell duration equalled 22 days. Furthermore, 19 events exceeding 10 mm were recorded (rainfall events >10 mm are commonly considered as productive rainfall events, [34]).…”

A deuterium-based labeling technique for the investigation of rooting depths, water uptake dynamics and unsaturated zone water transport in semiarid environments

“…Rather than that, the mechanism in our case could be explained as follows: In deep unsaturated zones (such as our study site) water needs many years to reach the groundwater table. Eventually, only extreme events or very wet seasons create recharge (Beyer et al, 2014;Evaristo et al, 2015;Taylor et al, 2013). This water, once reaching the groundwater, could be isotopically different from water present in the upper unsaturated zone (refer to Fig.…”

Response to Anonymous Referee #2

“…Bias-correction schemes evaluated in this study are the spatio-temporal bias (STB), elevation zone bias (EZ), power transform (PT), distribution transformation (DT), and quantile mapping based on an empirical distribution (QME), this by our aim to correct for bias while daily rainfall variability is preserved. The five schemes are chosen based on merits documented in the literature (Bhatti et al, 2016;Habib et al, 2014;Teutschbein and Seibert, 2013;Themeßl et al, 2012;Vernimmen et al, 2012). We note that findings on the performance of selected bias-correction schemes in literature do not allow for generalisation, but findings only apply to the respective study domains (Wehbe et al, 2017;Jiang et al, 2016;Liu et al, 2015;Haile et al, 2015).…”