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Università degli Studi di Napoli Federico II (2017)

AGROHYDROLOGICAL SIMULATION FOR MITIGATION AND MANAGEMENT OF SOIL MOISTURE DEFICIT IN RAINFED AGRICULTURE

Openy, Geoffrey

Titre : AGROHYDROLOGICAL SIMULATION FOR MITIGATION AND MANAGEMENT OF SOIL MOISTURE DEFICIT IN RAINFED AGRICULTURE

Auteur : Openy, Geoffrey

Université de soutenance : Università degli Studi di Napoli Federico II

Grade : Tesi di dottorato 2017

Résumé partiel
Drought is a natural disaster that occurs in all climatic regions, and is responsible for food insecurity in majority of developing countries. Globally, interventions to mitigate drought impacts have focused in semi-arid and arid areas. However, increased climatic variations have become more frequent in the recent past causing sporadic agricultural droughts with the end results being food shortages even in areas that receive relatively high rainfall. Many of such areas are occupied by vulnerable communities lacking strategic coping mechanisms for mitigation of drought impacts. The aim of this study was to develop a simplified approach for computing a Soil Moisture Deficit Index (SMDI) that integrates limited climatic records common in developing countries together with freely available tools for supporting soil water management decisions under rainfed agriculture. Most soil moisture based drought indices are derived from long term records of measured soil moisture time series. However, such long-term soil moisture records are scarcely available in African countries where they could be of greatest benefit in designing techniques for mitigating drought impacts. Therefore, the main objective of this research was to evaluate the performance of simulated soil moisture time series to develop a SMDI with minimal requirements of input data. To this aim, the study was organized in four consecutive objectives, namely : to identify and adapt a suitable drought indicator in relation to the data availability. Secondly, to assess the feasibility of using a calibrated agro-hydrological model for producing long time series of soil water dynamics and derive SMDI for monitoring agricultural droughts. The third objective was to upscale the SMDI through energy balance modeling using a case study in Northern Uganda. And the fourth objective was, to formulate a soil water management decision support scheme for mitigation of agricultural droughts in rain fed farming systems through application of SMDI. The study is based on agro-hydrological data collected in a dairy farm of 10 ha in Northern Uganda equipped with Mateo station and low cost commercial soil sensors to monitor soil water dynamics in the root zone during two seasons under rain fed maize crops in 2015. Because of the importance of Evapotranspiration in agro-hydrological studies and limited reported research on it at the study site, 13 different simplified reference evapotranspiration (ET0) models were compared with FAO-56 Penman-Monteith to select the best performing simplified model for application in the study area. Evaluation of the 13 ET0 models showed that the Makkink radiation model gave the best prediction of ET0 with Root Mean Squared Error (RMSE) = 0.6 mm, Mean Absolute Error (MAE) = 0.4 mm, Nash Sutcliffe Efficiency (NSE) = 0.8, Coefficient of Agreement (d) = 0.90 and Coefficient of Determination (r2) = 0.7. All temperature based models overestimated ET0 with Thornthwaite giving the worst prediction in all the test statistics.

Mots Clés  : drought index, soil moisture, evapotranspiration, Landsat, Uganda

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Page publiée le 29 avril 2020