Improvement of reference crop evapotranspiration estimates using limited data for the Brazilian Cerrado

Althoff, Daniel; Rodrigues, Lineu Neiva

doi:10.1590/1678-992X-2021-0229

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Brasil

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Sumário

Agrometeorology, Research Article • Sci. agric. (Piracicaba, Braz.) 80 • 2023 • https://doi.org/10.1590/1678-992X-2021-0229 copy

Improvement of reference crop evapotranspiration estimates using limited data for the Brazilian Cerrado

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Evapotranspiration (ET) is a key component of the hydrological cycle. Therefore, adequately estimating it is crucial to improving water resource planning and management.One of the most affordable methods of estimating ET is first to estimate reference crop evapotranspiration (ETo) and later associate it to crop and soil coefficients. The FAO Kc-ETo approach can be used only when ETo is computed with the FAO Penman-Monteith equation. However, low data availability may restict the equations used to estimate ETo. In this study, we assess and calibrate common methods used to estimate ETo under such conditions of limited data availability. Based on the annual calibration, the Makkink (NSE = 0.85) outperformed the Priestley-Taylor (NSE = 0.73), Hargreaves-Samani (NSE = 0.56), and Penman-Monteith temperature approach (NSE = 0.58). The seasonal calibration of parameters showed no significant improvement to the methods assessed (ΔNSE ≤ 0.01), except for the Priestley-Taylor (ΔNSE = 0.06). The performance of temperature-based equations was particularly limited due to the performance of the equation adopted to estimate global solar radiation. Thus, improving the representation of global solar radiation for limited data availability can also play a key role in improving ETo prediction.

Penman-Monteith temperature approach; tropical savannah; estimating dew-point temperature; average wind speed

INMET ID	Observations	Latitude	Longitude	Elevation
82296	5408	–3.47	–42.27	44.1
82298	4692	–3.90	–42.25	87.1
82474	3915	–4.28	–41.80	160.0
82476	4861	–4.87	–43.36	96.7
82480	7010	–4.28	–41.79	157.9
82564	5156	–5.54	–47.48	126.3
82571	6238	–5.51	–45.24	154.2
82578	4394	–5.03	–42.80	75.7
82659	7462	–7.10	–48.20	231.9
82676	4507	–6.03	–44.23	175.6
82678	6707	–6.76	–43.00	126.6
82768	6233	–7.53	–46.05	263.5
82861	6945	–8.26	–49.26	179.0
82863	6715	–8.97	–48.18	189.5
82970	6157	–9.11	–45.95	285.1
82975	5934	–9.07	–44.37	330.6
83033	7313	–10.19	–48.30	291.7
83064	5278	–10.71	–48.41	243.3
83228	7368	–12.02	–48.54	252.2
83270	6426	–13.47	–52.27	430.0
83319	6807	–14.70	–52.35	305.3
83332	3866	–14.09	–46.37	830.4
83334	4900	–14.95	–46.24	854.6
83358	6068	–15.83	–54.40	374.4
83363	4582	–15.82	–55.42	787.0
83364	7092	–15.78	–56.07	140.0
83368	7065	–15.90	–52.25	327.0
83373	5620	–15.93	–47.88	1100.6
83374	4469	–15.91	–50.13	512.2
83376	7473	–15.85	–48.97	766.9
83377	7416	–15.79	–47.93	1161.4
83379	7339	–15.55	–47.34	938.7
83388	4487	–15.08	–42.75	625.0
83437	5407	–16.69	–43.84	645.9
83452	5737	–16.78	–43.67	655.6
83464	6463	–17.92	–51.72	669.8
83470	6077	–17.79	–50.96	780.0
83479	7219	–17.24	–46.88	711.4
83483	5443	–17.35	–44.91	505.2
83531	6052	–18.51	–46.43	940.3
83533	5396	–19.71	–45.36	695.0
83538	5165	–18.23	–43.64	1296.1
83565	4474	–19.66	–51.19	429.6
83577	5954	–19.73	–47.95	737.0
83582	6042	–20.03	–46.00	661.3
83586	5279	–19.46	–44.25	732.0
83630	7365	–20.58	–47.38	1003.6
83635	7128	–20.17	–44.87	787.4
83669	6167	–21.46	–47.58	620.0
83726	5292	–21.98	–47.88	859.8
A001	6135	–15.79	–47.93	1161.0
A002	6107	–16.64	–49.22	727.3
A003	4412	–17.75	–49.10	751.1
A004	4452	–14.45	–48.45	583.0
A009	5173	–10.19	–48.30	291.9
A010	3751	–12.62	–47.87	285.0
A012	4908	–16.26	–47.97	1000.8
A013	4176	–15.90	–52.25	327.4
A014	4293	–15.94	–50.14	512.9
A015	4178	–14.98	–49.54	551.2
A016	4325	–17.92	–51.72	670.1
A017	4436	–14.09	–46.37	830.0
A018	4085	–12.02	–48.54	250.9
A019	4720	–11.75	–49.05	279.1
A020	4670	–8.97	–48.18	189.7
A021	3915	–7.10	–48.20	230.8
A022	3863	–15.22	–48.99	667.0
A023	4649	–16.97	–51.82	740.1
A024	3884	–14.13	–47.52	1264.7
A025	3914	–17.79	–50.96	780.1
A026	3784	–17.45	–52.60	862.0
A027	4257	–16.96	–50.43	678.7
A032	3874	–13.25	–46.89	551.3
A033	4268	–17.30	–48.28	757.3
A034	4265	–18.15	–47.93	900.7
A035	3934	–18.41	–49.19	491.2
A038	4197	–11.59	–46.85	727.9
A039	3726	–11.89	–49.61	215.2
A045	4104	–15.60	–47.63	1030.4
A205	3836	–7.34	–47.46	182.9
A221	3696	–5.51	–45.24	154.2
A223	4276	–9.11	–45.93	283.7
A224	3825	–6.65	–47.42	183.0
A225	4374	–5.56	–47.46	118.0
A237	3746	–4.82	–43.34	84.9
A241	3885	–8.30	–49.28	175.7
A311	4800	–6.76	–43.00	126.4
A312	3871	–5.03	–42.80	75.2
A346	4238	–7.44	–44.35	398.8
A363	3928	–6.40	–41.74	313.4
A402	5003	–12.12	–45.03	474.2
A404	5379	–12.15	–45.83	760.7
A505	5614	–19.61	–46.95	1018.3
A506	5903	–16.69	–43.84	645.9
A507	5552	–18.92	–48.26	874.8
A512	4633	–18.95	–49.53	540.1
A516	4164	–20.75	–46.63	781.7
A519	4526	–19.54	–49.52	559.1
A523	4867	–19.00	–46.99	978.1
A528	4532	–18.20	–45.46	931.0
A535	4512	–19.89	–44.42	753.5
A536	4354	–19.48	–45.59	721.1
A537	4791	–18.23	–43.65	1359.3
A538	4950	–18.75	–44.45	669.5
A541	4508	–17.71	–42.39	932.1
A542	4643	–16.55	–46.88	640.9
A544	4176	–15.52	–46.44	894.0
A545	4283	–17.26	–44.84	505.3
A546	4601	–17.56	–47.20	997.0
A547	4550	–16.36	–45.12	490.3
A548	4222	–15.30	–45.62	873.2
A551	4547	–15.72	–42.44	850.1
A702	5310	–20.45	–54.72	528.5
A703	4909	–22.55	–55.72	668.0
A704	4532	–20.78	–51.71	328.9
A705	4558	–22.36	–49.03	636.2
A708	5597	–20.58	–47.38	1002.7
A711	4166	–21.98	–47.88	859.3
A718	4135	–22.37	–50.97	398.8
A720	3943	–18.51	–54.74	251.5
A721	4036	–22.19	–54.91	463.3
A722	3727	–20.40	–56.43	132.5
A730	4016	–18.80	–52.60	820.8
A731	3750	–21.61	–55.18	388.9
A732	3706	–19.42	–54.55	646.0
A750	4036	–23.00	–55.33	433.6
A907	4721	–16.46	–54.58	289.9
A908	3796	–14.02	–52.21	440.0
A912	4169	–15.53	–55.14	748.3
A931	4066	–14.93	–53.88	664.2
A933	3684	–17.18	–54.50	593.1
A938	3805	–12.73	–60.16	583.3

Parameters	Original	Annual	Wet	Dry
a_T	0.00	–0.42	–0.93	0.57
u₂	2.00	1.23	1.17	1.31
k_Rs	0.160	0.159	0.155	0.165
offset	17.8	14.9	14.8	15.1
a	1.26	1.18	1.13	1.30
c₁	0.61	0.70	0.67	0.76
c₂	–0.12	0.10	0.28	–0.26

Escola Superior de Agricultura "Luiz de Queiroz" USP/ESALQ - Scientia Agricola, Av. Pádua Dias, 11, 13418-900 Piracicaba SP Brazil, Phone: +55 19 3429-4401 / 3429-4486 - Piracicaba - SP - Brazil
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[1] *Corresponding author <daniel_althoff@hotmail.com>