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No. of bitstreams: 1 PedroRodriguesMutti_DISSERT.pdf: 5339390 bytes, checksum: 305eafacbb12ac9dcc159c054075747f (MD5) Previous issue date: 2018-02-22 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / A Bacia Hidrogr?fica do Rio Piranhas-A?u (BHPA) est? inserida na regi?o do Semi?rido brasileiro, onde a ocorr?ncia de longos per?odos de estiagem associada aos conflitos na distribui??o dos recursos h?dricos impacta diretamente a disponibilidade de ?gua para abastecimento humano e para o desenvolvimento agr?cola da regi?o. Em virtude disso, o estudo dos processos do ciclo hidrol?gico ? fundamental para a tomada de decis?es no ?mbito do gerenciamento dos recursos h?dricos. Dentre estes processos a evapotranspira??o (ET) se destaca pelo seu papel fundamental nas intera??es entre ?gua, solo e vegeta??o, na modelagem hidrometeorol?gica e nos fluxos de energia em regi?es de clima semi?rido. O objetivo desse estudo ?, portanto, quantificar a ET di?ria em toda a regi?o da BHPA, em um ano seco e um ano chuvoso, utilizando dados de sensores orbitais e formula??es dos algoritmos Simplified Surface Energy Balance Index (S-SEBI) e Simplified Surface Energy Balance (SSEB). Foram utilizados dados de temperatura da superf?cie, albedo e NDVI obtidos pelo sensor orbital MODIS e dados de radia??o solar provenientes das esta??es meteorol?gicas inseridas na bacia. Realizou-se uma an?lise pluviom?trica com dados de precipita??o de postos inseridos na bacia que indicou o ano 2009 como sendo um ano chuvoso e o ano de 2012 como sendo um ano seco, sendo os mesmos escolhidos para quantifica??o da ET. O algoritmo proposto foi calibrado e validado utilizando dados dos elementos do balan?o de energia obtidos em uma torre de fluxo equipada com sistema de eddy covariance. As estimativas da ET di?ria apresentaram boa concord?ncia com os valores observados (R?=0,64, RMSE=0,79 mm.d-1) e o erro relativo da ET anual foi de 7,3% (33,7 mm.ano-1). Em 2009 as maiores taxas mensais de ET foram encontradas nos corpos h?dricos (96,4 mm) e nas regi?es de Caatinga (93,0 mm) em mar?o e abril. Nesse ano, as taxas mensais de ET mantiveram-se maiores que 30,0 mm em todas as classes de uso do solo at? outubro. Em 2012, as maiores taxas foram encontradas tamb?m em mar?o e abril, com destaque para os corpos h?dricos (100,9 mm) e a Caatinga (87,4 mm). Nesse ano, no m?s de junho as taxas de ET atingiram valores inferiores a 30,0 mm, com m?nimo em setembro nas regi?es de solo exposto (17,6 mm). O excedente/d?ficit h?drico foi calculado utilizando-se dados de precipita??o do sat?lite TRMM. No ano de 2009 foi observado um excedente h?drico de 721,5 mm na BHPA, uma magnitude 4,7 vezes maior que o d?ficit observado em 2012 (-153,2 mm). Isso indica que, desconsiderando-se o uso consuntivo dos recursos h?dricos na bacia, anos chuvosos t?m o potencial de compensar at? quatro anos de seca intensa. / The Piranhas-A?u River Basin (PARB) is located in Brazil?s semiarid region, where the occurrence of long draught periods associated with water resources allocation conflicts may put its water availability at risk, impacting human supply and agriculture development. Because of that, research on hydrological cycle processes is crucial to water resources management in water basins. Among these processes, evapotranspiration (ET) is of uttermost importance given its critical role in water, soil and vegetation interactions, hydrometeorological modelling and in the energy fluxes dynamics of semiarid regions. Therefore, the objective of this study is to quantify daily ET during a wet and a dry year in all the PARB, by using remote sensing data and formulations based on the Simplified Surface Energy Balance Index (S-SEBI) and the Simplified Surface Energy Balance (SSEB) algorithms. Land surface temperature, albedo and NDVI data from MODIS sensor and solar radiation data from weather stations located in the basin were used. Precipitation analysis was carried out using data from rain gauges located in the basin. It indicated 2009 as being an unusually wet year and 2012 as an unusually dry year, which were selected for the ET quantification. The proposed algorithm was calibrated and validated with energy balance components data from a flux tower equipped with eddy covariance system. Daily ET estimates showed good agreement with observed values (R?=0.64, RMSE=0.79 mm.d-1) and annual ET relative error was of 7,3% (33.7 mm.year-1). In 2009 the highest monthly ET rates were found in water bodies (96.4 mm) and in the Caatinga (93.0 mm) during March and April. In this year, ET monthly rates were higher than 30.0 mm in all land cover classes until October. In 2012, the highest rates were also found in March and April in water bodies (100.9 mm) and the Caatinga (87.4 mm). In June of this year monthly ET rates were as lows as 30.0 mm, with a minimum of 17.6 mm in bare soil areas in September. Water surplus was calculated using precipitation data from the TRMM satellite. During 2009 it was observed a surplus of 721.5 mm in the PARB, which was 4.7 times greater than the deficit observed in 2012 (-153.2 mm). This indicates that, neglecting consumptive water usage in the basin, wet years can potentially compensate up to four years of intense draughts.

Policy makers adopt irrigated agriculture for food security, since irrigation doubles crop production. Therefore, the development of large irrigation systems has a long history in many places worldwide. Although large-scale irrigation schemes play an important role in improving food security, many schemes, especially in Africa, do not yield the expected outcomes. This is related to poor water management, which is generally due to a lack of effective evaluation and monitoring. The objective of this study, therefore, is to propose a new methodology to assess, evaluate and monitor large-scale irrigation systems. Information on irrigation indicators is needed to enable the evaluation of irrigation performance. The evaluation is the first and the most significant step in providing information about how it is performing. After reviewing extensive literature, a list of indicators related to the performance of irrigation, rainwater supply and productivity is suggested. The irrigation efficiency indicators Relative Irrigation Supply (RIS) and Relative Water Supply (RWS) are selected. Potential rainwater supply to crops can be tested based on the Moisture Availability Index (MAI) and the Ratio of Moisture Availability (RMA). Water productivity can be assessed by Crop Yield (Y) and Water Use Efficiency (WUE). However, the central problem facing large-scale irrigation schemes is always the lack of data, which calls for the development of a new method of data acquisition that allows evaluation and monitoring. Remote Sensing (RS) technology makes it possible to retrieve data across large areas. Two different approaches via RS, the Normalized Difference Vegetation Index (NDVI) and Actual Evapotranspiration (ETa), can be utilized for monitoring. The well-known Vegetation Condition Index (VCI), derived from the NDVI, is modified (MVCI) to allow a qualitative spatio-temporal assessment of irrigation efficiency. MVCI takes into account crop response to water availability, while ETa indicates whether water is used as intended. Furthermore, the assessment of the possible hydrological impact of the irrigation system should be considered in the evaluation and monitoring process. The Sudanese Gezira Scheme of 8,000 square kilometers in the Nile Basin, where performance evaluation and monitoring are absent or poorly conducted, is no exception. This research takes the large-scale irrigation of the Gezira Scheme as a case study, as it is the largest scheme, not only in the Nile Basin but also in the world, under single management. The first long-term historical evaluation of the scheme is conducted for the period 1961–2012 rather than only on a short-time scale as is the common practice. An increase in RIS and RWS values from 1.40 and 1.70 to 2.23 and 2.60, respectively, since the 1993/94 season shows decreasing irrigation efficiency. MAI and RMA for summer crops indicate a promising rainfall contribution to irrigation in July and August. The Gezira Scheme achieves low yield and WUE in comparison to many irrigation schemes of the globe. Low productivity is mainly due to poor distribution and irrigation mismanagement. This is indicated by the 15-year MVCI spatio-temporal analysis, which shows that the northern part of the scheme experiences characteristic drought during the summer crop season. Although MVCI can be considered a monitoring tool, the index does not deduct the soil water content, and water could be wasted and available in other ways (e.g. water depressions). Spatio-temporal information for ETa is required to better quantify water depletion and establish links between land use and water allocation. However, several RS models have been developed for estimating ETa. Thus, improving the understanding of performance of such models in arid climates, as well as large-scale irrigation schemes, is taken into account in this study. Four different models based on the energy balance method, the Surface Energy Balance Algorithm for Land (SEBAL), Mapping EvapoTranspiration at High Resolution with Internalized Calibration (METRIC™), Simplified Surface Energy Balance (SSEB) and MOD16 ET are applied in order to determine the optimal approach for obtaining ETa. Outputs from these models are compared to actual water balance (WB) estimates during the 2004/05 season at field scale. Several statistical measures are evaluated, and a score is given for each model in order to select the best-performing model. Based on ranking criteria, SSEB gives the best performance and is seen as a suitable operational ETa model for the scheme. SSEB subsequently is applied for summer and winter crop seasons for the period 2000–2014. Unfortunately, one of the limitations faced in the current research is the absence of validation data on a regional scale. Therefore, the assessment focuses on spatial distribution and trends rather than absolute values. As with the MVCI distribution, the seasonal ETa for the Gezira Scheme is higher in the southern and central parts than in the northern part. This confirms the robustness of the developed MVCI. To avoid using absolute values of ETa, the ratio of ETa from agricultural areas (ETagr) to the total evapotranspiration (ET) from the scheme (ETsum) is calculated. The ETagr/ETsum ratio shows a descending trend over recent years, indicating that the water is available but not being utilized for agricultural production. This study shows that SSEB is also useful for identifying the location of water losses on a daily basis. Around 80 channels are identified as having leakage problems for the 2013/14 crop season. Such information is very useful for reducing losses at the scheme. In addition, Rainwater Harvesting (WH) is addressed and found to be applicable as an alternative solution for accounting for rainfall in irrigation. It is seen that these management scenarios could save water and increase the overall efficiency of the scheme. It is possible to save 68 million cubic meters of water per year when the overall irrigation efficiency of the scheme is improved by only 1%. A level of efficiency of 75% is predicted from the proposed management scenarios, which could save about 2.6 billion cubic meters of water per year. In conclusion, the present study has developed an innovative method of identifying the problems of large-scale schemes as well as proposing management scenarios to enhance irrigation water management practice. Improved agricultural water management in terms of crop, water and land management can increase food production, thereby alleviating poverty and hunger in an environmentally sustainable manner.

Policy makers adopt irrigated agriculture for food security, since irrigation doubles crop production. Therefore, the development of large irrigation systems has a long history in many places worldwide. Although large-scale irrigation schemes play an important role in improving food security, many schemes, especially in Africa, do not yield the expected outcomes. This is related to poor water management, which is generally due to a lack of effective evaluation and monitoring. The objective of this study, therefore, is to propose a new methodology to assess, evaluate and monitor large-scale irrigation systems. Information on irrigation indicators is needed to enable the evaluation of irrigation performance. The evaluation is the first and the most significant step in providing information about how it is performing. After reviewing extensive literature, a list of indicators related to the performance of irrigation, rainwater supply and productivity is suggested. The irrigation efficiency indicators Relative Irrigation Supply (RIS) and Relative Water Supply (RWS) are selected. Potential rainwater supply to crops can be tested based on the Moisture Availability Index (MAI) and the Ratio of Moisture Availability (RMA). Water productivity can be assessed by Crop Yield (Y) and Water Use Efficiency (WUE). However, the central problem facing large-scale irrigation schemes is always the lack of data, which calls for the development of a new method of data acquisition that allows evaluation and monitoring. Remote Sensing (RS) technology makes it possible to retrieve data across large areas. Two different approaches via RS, the Normalized Difference Vegetation Index (NDVI) and Actual Evapotranspiration (ETa), can be utilized for monitoring. The well-known Vegetation Condition Index (VCI), derived from the NDVI, is modified (MVCI) to allow a qualitative spatio-temporal assessment of irrigation efficiency. MVCI takes into account crop response to water availability, while ETa indicates whether water is used as intended. Furthermore, the assessment of the possible hydrological impact of the irrigation system should be considered in the evaluation and monitoring process. The Sudanese Gezira Scheme of 8,000 square kilometers in the Nile Basin, where performance evaluation and monitoring are absent or poorly conducted, is no exception. This research takes the large-scale irrigation of the Gezira Scheme as a case study, as it is the largest scheme, not only in the Nile Basin but also in the world, under single management. The first long-term historical evaluation of the scheme is conducted for the period 1961–2012 rather than only on a short-time scale as is the common practice. An increase in RIS and RWS values from 1.40 and 1.70 to 2.23 and 2.60, respectively, since the 1993/94 season shows decreasing irrigation efficiency. MAI and RMA for summer crops indicate a promising rainfall contribution to irrigation in July and August. The Gezira Scheme achieves low yield and WUE in comparison to many irrigation schemes of the globe. Low productivity is mainly due to poor distribution and irrigation mismanagement. This is indicated by the 15-year MVCI spatio-temporal analysis, which shows that the northern part of the scheme experiences characteristic drought during the summer crop season. Although MVCI can be considered a monitoring tool, the index does not deduct the soil water content, and water could be wasted and available in other ways (e.g. water depressions). Spatio-temporal information for ETa is required to better quantify water depletion and establish links between land use and water allocation. However, several RS models have been developed for estimating ETa. Thus, improving the understanding of performance of such models in arid climates, as well as large-scale irrigation schemes, is taken into account in this study. Four different models based on the energy balance method, the Surface Energy Balance Algorithm for Land (SEBAL), Mapping EvapoTranspiration at High Resolution with Internalized Calibration (METRIC™), Simplified Surface Energy Balance (SSEB) and MOD16 ET are applied in order to determine the optimal approach for obtaining ETa. Outputs from these models are compared to actual water balance (WB) estimates during the 2004/05 season at field scale. Several statistical measures are evaluated, and a score is given for each model in order to select the best-performing model. Based on ranking criteria, SSEB gives the best performance and is seen as a suitable operational ETa model for the scheme. SSEB subsequently is applied for summer and winter crop seasons for the period 2000–2014. Unfortunately, one of the limitations faced in the current research is the absence of validation data on a regional scale. Therefore, the assessment focuses on spatial distribution and trends rather than absolute values. As with the MVCI distribution, the seasonal ETa for the Gezira Scheme is higher in the southern and central parts than in the northern part. This confirms the robustness of the developed MVCI. To avoid using absolute values of ETa, the ratio of ETa from agricultural areas (ETagr) to the total evapotranspiration (ET) from the scheme (ETsum) is calculated. The ETagr/ETsum ratio shows a descending trend over recent years, indicating that the water is available but not being utilized for agricultural production. This study shows that SSEB is also useful for identifying the location of water losses on a daily basis. Around 80 channels are identified as having leakage problems for the 2013/14 crop season. Such information is very useful for reducing losses at the scheme. In addition, Rainwater Harvesting (WH) is addressed and found to be applicable as an alternative solution for accounting for rainfall in irrigation. It is seen that these management scenarios could save water and increase the overall efficiency of the scheme. It is possible to save 68 million cubic meters of water per year when the overall irrigation efficiency of the scheme is improved by only 1%. A level of efficiency of 75% is predicted from the proposed management scenarios, which could save about 2.6 billion cubic meters of water per year. In conclusion, the present study has developed an innovative method of identifying the problems of large-scale schemes as well as proposing management scenarios to enhance irrigation water management practice. Improved agricultural water management in terms of crop, water and land management can increase food production, thereby alleviating poverty and hunger in an environmentally sustainable manner.